Summer 2026
Engineering Intern
Pipeline Observability and Lineage
Posted on 4/3/2026
Actian
501-1,000 employees
Offers data management and analytics platforms
Compensation Overview
$20 - $30/hr
Remote in USA
Remote
Bachelor's, Master's
 Software Engineering (1) |
|---|
Get referred to Actian
See people who can refer or advise you
- Must be actively enrolled in a college degree program
- Must be legally authorized to work in the United States
- Collaborate with the engineering team to design and implement new features using Java and modern development practices.
- Utilize AI-based tools like Claude to assist in code generation and improve development efficiency.
- Capstone Project: Develop a new receiver for various data pipelines using AI-assisted coding plugins.
- Actively pursuing a Bachelor’s or Master’s degree in Computer Science or a related field.
- Strong proficiency in Java and familiarity with version control systems like Git.
- Previous experience with full-stack development or cloud platforms (AWS/Azure) is a plus.
Actian provides data management and analytics tools that help organizations connect to data, analyze it quickly, and act on insights. Key products include Actian Avalanche, a fully managed hybrid-cloud data warehouse; Actian DataCloud for data integration; Actian X for operational analytics, integration, and monitoring; and specialized databases Vector for high-performance analytics and Zen for embedded/IoT use cases. These tools connect to multiple data sources, process data in real time, and let users run queries and dashboards to derive insights. Actian differentiates itself by offering both on-premises and cloud options within an integrated suite that covers ingestion, storage, analytics, and monitoring, enabling real-time insights across traditional databases and edge/IoT scenarios.
Company Size
501-1,000
Company Stage
Series E
Total Funding
$84.5M
Headquarters
Redwood City, California
Founded
2005
Get referred to Actian
See people who can refer or advise you
Simplify's Take
What believers are saying
- July 2026 Jaspersoft integration adds 1,000 customers and 90 partners across 44 countries.
- June 2026 Data Steward Agent reduces manual metadata work and accelerates AI-ready governance.
- August 2026 product updates add DataConnect 14.0, Zen 17 AI, and AI Analyst enhancements.
What critics are saying
- Snowflake, Databricks, and Collibra expanded governance and agent controls in June 2026.
- Actian's acquisitions of Wobby and Jaspersoft create integration risk through 2027.
- HCLSoftware owns Actian; a parent-level strategy shift can bury the brand or starve R&D.
What makes Actian unique
- Actian bundles governance, analytics, and reporting across Ingres, Zen, and Jaspersoft.
- Its federated knowledge graph powers governed semantics for AI agents and natural-language analytics.
- Legacy database depth keeps Actian embedded inside regulated, operational workloads others ignore.
Help us improve and share your feedback! Did you find this helpful?
Benefits
Health Insurance
Parental Leave
Paid Vacation
Professional Development Budget
Conference Attendance Budget
Wellness Program
Growth & Insights and Company News
6 month growth
↑ 12%1 year growth
↑ 12%2 year growth
↑ 12%What is a data product and why does your AI strategy depend on it? Summary. * Data products are becoming essential because AI systems need trusted, well-governed, and reusable data to work reliably. * A data product is more than a dataset: it has purpose, ownership, quality standards, governance, and lifecycle management. * The rise of AI is making weak data foundations more visible because AI cannot reliably spot bad data the way humans often can. * Data contracts matter too because they define the structure, quality, and expectations consumers can rely on over time. * The core message is that organizations succeeding with AI are not just collecting data, but packaging it into trusted data products. Your organization has spent years investing in technologies to collect, integrate, govern, and analyze data. So why does it feel like the people and systems that need it most can't trust it? With AI now moving from experimentation to production at many organizations, solving that issue is becoming even more urgent. AI models, copilots, and agents depend on data. If that data is incomplete, inconsistent, poorly documented, or difficult to access, AI systems can produce inaccurate answers, unreliable recommendations, and costly mistakes. That's why the conversation around data products has gone from "nice to have" to "we need to figure this out now." According to recent research from BARC and Actian, data product adoption increased from 48% in 2024 to 69% in 2026. That's not a trend. It's a signal that's hard to ignore. What is a data product? A data product is a curated, governed, and reusable data asset. It's designed to deliver value to a specific group of consumers, whether that's a business analyst, an application, or an AI agent pulling answers every day at 2 AM. "Data products are assets that help organizations take control of their data and generate business value," according to Deloitte. "They are shareable and can help unlock the potential of data in a way that benefits both internal and external customers." Unlike a traditional dataset, a data product has: * A clearly defined purpose. * Documented business meaning. * Known ownership. * Quality standards. * Service expectations. * Governance controls. * Ongoing lifecycle management. Here's a way to think about it: raw data is like ingredients. You can technically make something from it, but you have to figure out what goes with what, what's expired, and what the recipe even is. A data product is like the prepared meal. It's ready to consume: packaged with the context, quality, and governance needed to actually make it useful. So instead of handing your AI systems a pile of ingredients and hoping for the best, you're giving them a trusted, documented, and ready-to-use asset. A real example is a Customer 360 data product that combines customer records from CRM, billing, support, and marketing systems into a single trusted view of each customer. Business users can then analyze it, applications can consume it, and AI systems can use it without having to reconcile conflicting records from multiple sources. Why AI changes the data conversation. Human analysts could often spot questionable data. They'd notice when a number looked off, dig into it, and flag the issue before it became a business decision. AI systems don't work that way. They generate content, answer questions, make recommendations, and increasingly take action based on the data they receive, even when that data is not fit for purpose. That's the uncomfortable truth behind why 60% of organizations in the BARC and Actian research cited "trustworthy data for AI use cases" as a primary driver for implementing data products. Ensuring trustworthy data is a way to implement damage control before something goes sideways. The good news? Enterprises have gotten this concept right and are seeing real results. GEMA, for example, deployed the Actian Data Intelligence Platform and built more than 400 certified data products, with 11 AI models running in production, achieving 140% ROI and over €1M per year in cost savings. Why 'we have data' isn't the same as 'we have data products' Most organizations often have thousands of tables, reports, dashboards, and datasets. That doesn't necessarily mean they have data products, and the gap matters. Traditional data assets often suffer from common challenges: * Unclear ownership. * Inconsistent definitions. * Unknown lineage. * Duplicate versions. * Limited documentation. * Manual governance. Data products flip the question. Instead of asking, "How do we store this data?" you start asking, "How will consumers use this data, and what do they need in order to trust it?" The shift alone changes how data teams operate. At Groupe BPCE, the approach led to over 80,000 business terms defined and more than 1,000 unique data explorers a week, turning a traditional siloed data function into something the whole organization can access and act on. What makes a good data product? Not all data products are created equal. The ones that hold up under pressure, including AI workloads, tend to share a few characteristics: * Business context. Consumers understand what the data represents and how it should be used. * Ownership. Someone is accountable for the quality, usability, and ongoing evolution of the data product. * Discoverability. Users can easily find and access the data product without relying on IT or manual requests. * Trust. Quality standards, lineage, and governance controls help consumers understand whether the data is fit for the intended purpose. * Reusability. The same data product can support multiple business use cases instead of requiring each team or user to recreate products using the same data. * Observability. Teams can monitor quality, detect issues, and maintain confidence as data changes over time. Enter data contracts: the other half of the equation. As organizations scale data products across teams and business domains, another critical factor emerges: a clear agreement between producers and consumers on what they're actually committing to. That's what a data contract is. It defines the structure, ownership, quality requirements, and operational expectations of a data product. When a downstream application, dashboard, or AI agent depends on that product, a contract is what gives them confidence that the data will still be what they expect next week. The BARC and Actian research found that data contract adoption is closely following data product adoption, with many organizations viewing contracts as a critical component of trust, governance, and quality management. Together, data products and data contracts create the foundation for scalable AI. The numbers make a pretty strong argument. If you're still weighing whether this is worth the investment, consider this: 85% of organizations with company-wide data products have three or more AI projects in production. That's not a coincidence. Data product strategies correlate strongly with agentic AI systems operating in production environments. This is the kind of autonomous AI that can drive business outcomes, not just answer questions in a chat box. The organizations moving fastest on AI aren't collecting more data. They're making the data they already have understandable, reliable, and ready to use. The era of AI does not tolerate messy data foundations. The good news is no one needs to start over. They just need to be deliberate about how data gets packaged, governed, and delivered. See how to create trusted, contract-governed data products on a platform that makes it easy to discover, trust, and activate data. Data insights delivered to you. Subscribe for Actian email updates.
Actian, the data and AI division of HCLSoftware, has integrated Jaspersoft's embedded analytics and reporting capabilities into its data management portfolio following HCLSoftware's acquisition of Jaspersoft. The company plans to enhance Jaspersoft with AI-enhanced analytics, agentic BI capabilities, and deeper integration across Actian's offerings. Jaspersoft serves approximately 1,000 customers globally and brings around 90 partners across 44 countries to Actian's network. The platform specialises in creating reports, interactive dashboards, and visualisations for regulated industries including financial services, healthcare, government, manufacturing, and technology. "With the addition of Jaspersoft, we're expanding our portfolio to support both, giving customers a seamless path from data to reporting, analytics, and AI-driven insight," said Marc Potter, chief executive officer of Actian.
HCLSoftware completes Jaspersoft acquisition, expands AI and data business. The acquisition brings Jaspersoft's analytics platform, around 1,000 customers and 90 global partners into HCLSoftware's data and AI business, as the company looks to expand its artificial intelligence offerings. By Navneet Singh July 7, 2026, 8:50:33 PM IST (Published) HCLSoftware has completed the acquisition of Jaspersoft, with the embedded analytics and reporting platform becoming part of Actian, the company's data and AI division. The company said Jaspersoft's embedded analytics and reporting capabilities will be integrated with Actian's data management portfolio. Top Gainers Top Losers Most Active Price Shockers Volume Shockers | Company | Value | Change | %Change | | Share India Securities Ltd. ₹164.91 | 27.48 | 20.00 | | India Tourism Development Corporation Ltd. ₹702.80 | 117.10 | 19.99 | | IOL Chemicals and Pharmaceuticals Ltd. ₹165.04 | 20.58 | 14.25 | | Kothari Industrial Corporation Ltd. ₹178.79 | 18.46 | 11.51 | | Physicswallah Ltd. ₹148.78 | 13.68 | 10.13 | Actian will continue to develop Jaspersoft's roadmap, with planned enhancements including AI-enhanced analytics, agentic business intelligence capabilities, and deeper integration across its portfolio. As part of the integration, Jaspersoft's approximately 90 partners across 44 countries will join Actian's network, alongside the platform's customer base of around 1,000 enterprise, mid-market and small business customers globally. According to the company, Jaspersoft is used across industries including financial services, healthcare, government, manufacturing and technology. In a sepretae filing, company said that it will announce its financial results for the first quarter of FY27, ended June 30, 2026, on Monday, July 13, after the close of Indian stock markets. Following the results announcement, the company's senior management will host a 60-minute audio conference call at 7:30 p.m. Q4FY26 results HCLTech had reported net profit of ₹4,488 crore, up 10.1% sequentially and 4.2% year-on-year, but below the CNBC-TV18 poll estimate of ₹4,696 crore. Revenue came in at ₹33,981 crore, up 0.3% quarter-on-quarter and 12.4% YoY, also missing the poll estimate of ₹34,553 crore. In dollar terms, revenue stood at $3.68 billion, rising 2.9% sequentially, but below expectations of $3.76 billion. Operating performance was weaker, with EBIT at ₹5,620 crore, down 10.6% QoQ, compared to estimates of ₹6,040 crore. EBIT margin came in at 16.5%, declining from 18.6% in the previous quarter and below expectations of 17.6%. Shares of HCL Technologies ended 3.16% higher at ₹1,170 on the NSE on Tuesday, July 7.
Actian adds Jaspersoft: completing the data value chain. Summary. * Actian finalized its strategic acquisition of Jaspersoft to fully unify the data value chain from raw ingestion to business application execution. * Jaspersoft provides a heavily downloaded open-source reporting engine alongside commercial embedded analytics frameworks across more than 75 countries. * Adding native pixel-perfect reporting and visualization layers allows current Actian clients to build charts without initiating separate integration projects. * Actian is maintaining Jaspersoft's open-source library roots, developer forums, and community channels while injecting deep product engineering investments. Actian has a straightforward yet ambitious vision: to shape the future of business with AI-ready data that is trusted, flexible, and easy to use. Actian Corporation do that by helping enterprises manage the entire data value chain. Not just part of it, all of it. From data collection and storage to governance, visualization, and activation to drive decisions and outcomes. Now, its ambitions take a significant step forward. Actian has completed its acquisition of Jaspersoft, the world's leading platform for embedded analytics and pixel-perfect reporting. Why Jaspersoft. Jaspersoft has been solving one of enterprise data's most persistent problems since 2001: getting trusted, accurate, precisely formatted data into the hands of the people who need to act on it. Its JasperReports Library is one of the most downloaded open-source projects in the world, with more than one million downloads every month. Its commercial platform is embedded inside enterprise applications across financial services, healthcare, government, and manufacturing, in 75+ countries, with an average customer tenure of nearly a decade. That kind of depth doesn't happen by accident. It happens when a product genuinely solves a problem at scale. For Actian, the fit is clear. Actian's portfolio already covers the majority of the data value chain - DataConnect for data integration and quality, Ingres, HCL Informix, Zen, and VectorAI DB for storage, and Data Intelligence and Data Observability for governance, and AI Analyst to engage and activate data. What was missing was the "Visualize" layer: the capability that takes governed, trusted data and delivers it as actionable insight to the business users who need it. Jaspersoft is that layer. What this means for customers. For existing Jaspersoft customers, this acquisition means one thing above all else: investment. Jaspersoft is joining Actian not to be folded into something else, but to be accelerated. The product team, engineering organization, and customer support teams are joining Actian intact. The roadmap is being funded with the backing of HCLSoftware, Asia's largest enterprise software company, and its $14.7 billion parent organization, HCLTech. The specific areas of investment reflect where enterprise analytics is heading, and Jaspersoft users will be among the first to benefit. Soon, Actian will deliver Agentic BI capabilities directly within the Jaspersoft platform. That means moving beyond scheduled reports and static dashboards to AI-driven analytics that works the way your business does: ask a question in plain language, get a governed, accurate, pixel-perfect answer, without a data analyst in the loop for every request. For enterprises already relying on Jaspersoft for operational reporting, this isn't a disruption to what you have. It's the next layer on top of it. For Actian's existing customers, the addition of Jaspersoft means the data platform they already rely on now includes a visualization and reporting capability, without adding a separate vendor or integration project. A community worth investing in. One of the most compelling aspects of the Jaspersoft acquisition is its developer community. More than one million community members have built on JasperReports Library over 25 years. That community is a reflection of what the technology actually delivers. After all, developers don't stay engaged with platforms that don't work. The open source foundation stays. JasperReports Library remains available. The Jaspersoft community forum remains active. The investment being made is additive and builds on top of a foundation that already has the trust of developers and enterprises around the world. The road ahead. Actian has always given enterprises a complete, governed path from raw data to business decisions. With Jaspersoft, that becomes even easier. The combined solutions span every step: Connect | Store | Govern | Visualize | Activate. Actian provides the full stack, with the depth, performance, and enterprise-grade reliability each step demands. Jaspersoft customers, Actian customers, and the broader Jaspersoft developer community are welcome to learn more and join the upcoming customer webinar. This is a significant moment for Actian. More importantly, it is the beginning of a significant period of investment for Jaspersoft and the customers who have trusted it for 25 years. Data insights delivered to you. Subscribe for Actian email updates.
Actian has launched the Data Steward Agent, an AI agent embedded in its Data Intelligence Platform that automates metadata documentation, enrichment and governance across enterprise AI systems. The agent maintains semantic consistency for internal workflows, MCP-connected tools and third-party AI agents. According to Gartner, 51% of organisations rely on passive metadata practices, with data stewards typically allocating only 5% to 10% of their time to governance tasks. The Data Steward Agent addresses this bottleneck by continuously monitoring data landscapes and automating metadata management across catalogues. Grounded in Actian's federated knowledge graph and semantic layer, the agent uses natural language processing to suggest updates aligned with existing data products and contracts. Data stewards review and approve suggestions, focusing on validation rather than manual creation.