Full-Time

Data Engineer

Rearc

Rearc

11-50 employees

Engineering services for GenAI, data, AWS

No salary listed

Bengaluru, Karnataka, India

Hybrid

Category
Data & Analytics (1)
Required Skills
Microsoft Azure
Airflow
BigQuery
Apache Spark
ETL
Data Engineering
Requirements
  • 2+ years of experience in data engineering, data architecture, or related fields, bringing valuable expertise in managing and optimizing data pipelines and architectures.
  • Solid track record of contributing to complex data engineering projects, including assisting in the design and implementation of scalable data solutions.
  • Hands-on experience with ETL processes, data warehousing, and data modelling tools, enabling the support and delivery of efficient and robust data pipelines.
  • Good understanding of data integration tools and best practices, facilitating seamless data flow across systems.
  • Familiarity with cloud-based data services and technologies (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery) ensuring effective utilization of cloud resources for data processing and analytics.
  • Strong analytical skills to address data challenges and support data-driven decision-making.
  • Proficiency in implementing and optimizing data pipelines using modern tools and frameworks.
  • Strong communication and interpersonal skills enabling effective collaboration with cross-functional teams and stakeholder engagement.
Responsibilities
  • Collaborate with Colleagues: Work closely with colleagues to understand customers' data requirements and challenges, contributing to the development of robust data solutions tailored to client needs.
  • Apply DataOps Principles: Embrace a DataOps mindset and utilize modern data engineering tools and frameworks like Apache Airflow, Apache Spark, or similar, to create scalable and efficient data pipelines and architectures.
  • Support Data Engineering Projects: Assist in managing and executing data engineering projects, providing technical support and contributing to project success.
  • Promote Knowledge Sharing: Contribute to our knowledge base through technical blogs and articles, advocating for best practices in data engineering, and fostering a culture of continuous learning and innovation.

Rearc provides engineering-driven services to help enterprises accelerate GenAI, data platforms, and cloud development, with a focus on AWS as an Advanced Consulting Partner. Teams assess current data and AI goals and design and implement end-to-end AWS-based solutions, including data pipelines, GenAI tooling, MLOps, and security/compliance. It differentiates itself through deep engineering in the AWS ecosystem and a proven track record with regulated industries, offering bespoke, end-to-end services rather than off-the-shelf software. The goal is to enable enterprises to rapidly adopt scalable, secure GenAI and cloud platforms that drive measurable business outcomes while meeting regulatory constraints.

Company Size

11-50

Company Stage

N/A

Total Funding

N/A

Headquarters

New York City, New York

Founded

2016

Simplify Jobs

Simplify's Take

What believers are saying

  • Financial firms deploy proprietary LLMs, boosting MLOps demand to $15B by 2026.
  • Healthcare AI diagnostics scale under FDA 2024 guidance, needing compliance consulting.
  • Data mesh architectures standardize, requiring federated platform design services.

What critics are saying

  • AWS expands consulting, compressing Rearc margins within 6-12 months.
  • GenAI commoditization via Bedrock erodes bespoke premiums in 6-12 months.
  • Talent attrition to Accenture and Deloitte hits within 12-24 months.

What makes Rearc unique

  • Rearc specializes in bespoke LLM and MLOps for financial services enterprises.
  • Engineers from Wall Street Journal founding drive cloud-native expertise since 2016.
  • AWS Advanced Partner status enables specialized GenAI platform acceleration.

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Benefits

Health Insurance

401(k) Retirement Plan

401(k) Company Match

Paid Vacation

Parental Leave

Professional Development Budget

Remote Work Options