Consultant - Data Engineer + AI
About the job
- The candidate must have 4–6 years of experience.
- The candidate must have a bachelor's degree in computer science engineering or equivalent work experience.
- The candidate must have knowledge of solution design, planning, development, and deployment of complex solutions.
- The candidate must have hands-on experience in data engineering across cloud, on-premises, and hybrid environments.
- The candidate must have foundational experience with Azure Data Services and data platform modernization initiatives.
- The candidate must have hands-on exposure to data warehousing and analytics using platforms such as Microsoft Fabric and Azure Synapse Analytics.
- The candidate must have experience or knowledge of one or more SQL and NoSQL database systems.
- The candidate must have hands-on experience building AI-powered data pipelines using ETL/ELT tools such as Azure Data Factory, SQL Server Integration Services, Talend, Informatica, or Airflow.
- The candidate must have exposure to data migrations, platform upgrades, and modernization efforts.
- The candidate must understand multitenant data platform designs, basic security hardening, and access control concepts.
- The candidate must have knowledge of big data ecosystems such as Spark, Databricks, Kafka, and Hadoop.
- The candidate must have experience building or supporting machine-learning-ready datasets and basic feature engineering.
- The candidate must have exposure to operationalizing machine learning pipelines and MLOps concepts on the Azure stack.
- The candidate must have foundational knowledge of large language models, model training, evaluation and deployment workflows, and the Azure cloud and AI stack.
- The candidate must have hands-on experience or knowledge in natural language processing, document intelligence and indexing, computer vision, retrieval-augmented generation frameworks or AI Search, or prompt engineering.
- The candidate must have exposure to or knowledge of deep learning and generative AI frameworks such as TensorFlow or PyTorch, and orchestration frameworks such as LangChain or LangGraph.
- The candidate must be familiar with responsible AI principles, including fairness, interpretability, and governance.
- The candidate must have experience working in Agile teams with knowledge of or exposure to Azure DevOps.
- The candidate must understand DataOps and MLOps practices, automated testing, continuous integration and continuous delivery pipelines, and deployment workflows.
- The candidate must have knowledge of secure coding practices, observability basics, and performance considerations.
- The candidate must have hands-on programming experience, preferably in Python.
- The candidate must be able to work closely with senior consultants, architects, and customers to co-create solutions addressing business challenges.
- The candidate must have strong communication skills to explain technical concepts to business stakeholders.
- The candidate must be comfortable working in ambiguous environments, learning quickly, and adapting to change.
- The candidate must be willing to build engineering excellence, reusable components, and best practices.
- The candidate must have a strong interest in continuous learning and technical certifications.
- The candidate must be curious to explore emerging data and AI technologies.
- The candidate must be willing to receive feedback, grow technical depth, and expand ownership over time.
- The consultant works as an individual contributor and key member of the Data and AI team, executing assigned deliverables with accurate estimates and work priorities while accommodating project changes and trade-offs.
- The consultant applies technical experience and industry-specific knowledge to develop solutions based on how proposed approaches affect customer and partner business objectives.
- The consultant helps design, develop, and deploy solutions on Microsoft technologies and methodologies.
- The consultant contributes to the technical delivery quality and overall efficacy of project teams within assigned engagements.
- The consultant defines dependencies and risks beyond the immediate scope and timeframe of complex projects, develops contingency plans and risk-mitigation criteria, and manages technical escalations.
- The consultant drives opportunities to expand or accelerate adoption of cloud and Microsoft technologies and collaborates with peers and account-aligned teams to scale business with strategic customers.
- The consultant aligns with innovation and digital transformation initiatives, ensures use of existing intellectual property, and delivers customer value.
- The consultant implements the technology strategy with support from senior peers.
- The consultant applies information-compliance and assurance policies to maintain stakeholder confidence.
- The consultant drives new ways of thinking across the division and subsidiary to improve quality, engineering productivity, and responsiveness to feedback and changing priorities.
- The consultant upskills through regular training and certifications on Azure Data and AI to contribute to future organizational and customer needs.
- Higher relevant education is preferred.
- Azure Databricks experience is a plus.
- One or more of the following certifications, or an equivalent industry certification, is a plus: Microsoft Certified: Azure Data Engineer Associate, Microsoft Certified: Azure AI Engineer Associate, or Microsoft Certified: Azure Solutions Architect Expert.
- Good understanding of core data architecture patterns, including dimensional modeling, Lambda and Kappa architectures, and time-series data processing.
- Familiarity with Azure Stream Analytics and Azure Analysis Services.
- Awareness of data governance concepts and tools.
About the company
Microsoft builds workplace software, operating systems and cloud infrastructure for consumers, businesses and government agencies, from small organizations to global enterprises. Microsoft 365 combines Word and Excel with Teams communication and Copilot AI features, while Windows runs PCs and Surface supplies the company's own computers. Azure rents computing capacity, storage and databases to build and run web applications. Microsoft also sells Xbox consoles and games, collecting revenue through software licenses, subscriptions, usage charges and product sales. Founded in 1975 by Bill Gates and Paul Allen, Microsoft is headquartered in Redmond, Washington.
Company Size
10,001+
Company Stage
IPO
Headquarters
Redmond, Washington
Founded
1975
Get referred to Microsoft
See people who can refer or advise you
Simplify's Take
What believers are saying
- US corporate staff receive education support: eligible, approved graduate coursework qualifies for up to $10,000 annually.
- Cloud demand expands: July 2026 results showed Azure and other cloud services revenue grew 43% year-over-year in fiscal Q4.
- Investment has an earnings cushion: July 2026 results reported $155.2 billion consolidated operating profit for fiscal 2026.
What critics are saying
- Performance reviews include security: every Microsoft employee must discuss their security contribution with their manager.
- Office flexibility depends on the role: Microsoft's postings specify requirements ranging from fully remote to fully on-site.
- Cloud capacity faces local limits: Microsoft describes power-grid delays and water constraints affecting US datacenter expansion.
What makes Microsoft unique
- Hybrid customers stay within reach: Azure Arc manages servers across customer datacenters and competing clouds.
- Developer reach extends beyond Azure: Microsoft's GitHub hosts code collaboration alongside AI coding tools.
- Professional data widens its business: Microsoft owns LinkedIn's recruiting, advertising and workplace-learning network.
Help us improve and share your feedback! Did you find this helpful?
Benefits
Health Insurance
Dental Insurance
Vision Insurance
401(k) Company Match
Professional Development Budget
Conference Attendance Budget
Flexible Work Hours
Remote Work Options
Growth & Insights and Company News
6 month growth
0%1 year growth
0%2 year growth
0%Ensure Endpoint Technologies has made PosturePass available in Microsoft Marketplace. The app lets organisations check the security of contractor and bring-your-own-device (BYOD) devices through their existing Microsoft Entra ID Conditional Access policies. Contractors install the app themselves, with no device-management enrolment, administrator rights, or IT ticket. It checks disk encryption, antivirus, firewall status, operating system patches, remote access software, and password policy. Once a device passes, PosturePass sends a compliance signal to Microsoft Entra ID, which can then grant access. Roughly one-quarter of devices fail at least one check during initial rollout. Most owners fix the problems without help-desk involvement. PosturePass is used across thousands of devices at insurance and financial services firms. Organisations can buy it through Microsoft Marketplace, including via private offers.
Apple, Amazon, and Microsoft have each unveiled AI devices in the past week, hoping to bring generative AI into homes before the holidays. Analysts expect modest sales for now, as weak consumer sentiment and rising component costs weigh on the market. Microsoft showed a Windows laptop from $2,599 with an RTX Spark chip that runs AI without the cloud. Amazon's largest Alexa Tablet 12 Pro costs $550, and its new Alexa requires a $19.99 monthly subscription or Prime membership. Apple's HomeView smart home hub costs $299 and has a 7-inch screen and facial recognition. Its $1,999 folding iPhone Duo reaches stores next week. IDC analyst Jitesh Ubrani said the aim is to get devices into homes and teach users, laying groundwork for bigger launches.
Investor Michael Burry, known for calling the 2008 housing crash, has warned that Microsoft and other big tech firms carry roughly $3 trillion in off-balance-sheet AI data-center liabilities. He said the companies are spending heavily because they assume they will get an oligopoly "too big to fail." Microsoft's capital spending in the June quarter was $41 billion, up 70% from a year ago. Its commercial remaining performance obligations, or contracted revenue not yet recognised, exceed $678 billion. Fourth-quarter revenue rose 18% to $90 billion, and net income rose 31% to $35.8 billion. Azure passed $100 billion in annual revenue. Shares are up 41% in three months. Analysts' consensus rating is "Strong Buy," with an average price target of $577.98.
Arena Physica has made Heaviside, its foundation model for electromagnetism, available on Microsoft Discovery, Microsoft's platform for agentic engineering. The company announced the move on October 13, 2026. Heaviside-1 has 350 million parameters and was trained on 250,000 3D field simulations. It predicts a design's full 3D electromagnetic field response in milliseconds, roughly 100,000 times faster than a traditional solver, and within a decibel of commercial accuracy. Traditional solvers can take hours or days per run, which makes design verification the main bottleneck. On Discovery, an agent can switch between Heaviside's predictions and a full-fidelity solver for final validation. Arena Physica expects strong uptake in semiconductors, including BGA packaging and SerDes interconnects. Discovery also offers audit logging and access controls to protect sensitive designs.
Venture capitalist Chamath Palihapitiya said power and physical infrastructure could be the lasting constraints in the AI race. He posted on X on Monday, after Microsoft announced its own silicon chips. Palihapitiya wrote that chipmakers will move up the stack while application companies move down it, so "everyone competes with everyone." He asked whether distribution, a data moat, or a physical limit such as power would support long-term margins. Elon Musk replied that scaling power, fast construction, cooling, networking, and batteries "is hard." Microsoft chief executive officer Satya Nadella said the company will scale its Maia chips to multi-gigawatt deployments starting next year. He said the Maia 300 delivers 40% more tokens per watt than leading GPU-based systems.