Data Engineer

Sentinel Group is seeking a Data Engineer (hybrid) to build, maintain, enhance, and integrate secure, scalable data pipelines and platforms. The role owns the data engineering lifecycle from architecture and modeling through validation, troubleshooting, and releases.

Responsibilities

• Lead the design, development, and ongoing evolution of end-to-end data pipelines, integrations, data models, and platform capabilities.
• Own production data systems and help drive their availability through monitoring, incident response, root-cause analysis, and continuous improvement.
• Develop and maintain a long-term vision for Sentinel’s data landscape.
• Translate business and technical requirements into clear architecture, implementation plans, and incremental deliverables.
• Design and implement scalable ETL/ELT workflows to ingest, transform, validate, and deliver data from APIs, databases, files, and other systems.
• Define and continuously improve standards for data quality, testing, documentation, lineage, observability, security, governance, and access control.
• Review architecture, technical designs, pull requests, and operational changes to identify risks and improve maintainability and performance.
• Lead modernization efforts for legacy data processes, moving toward secure, automated, cloud-based solutions aligned with Sentinel’s CI practices.
• Diagnose complex data, pipeline, performance, and reliability issues and drive both immediate remediation and durable prevention.
• Optimize queries, storage, processing, and infrastructure to improve performance, scalability, and cost efficiency.
• Collaborate with Business Analysts, Data Analysts, Software Engineers, Product Owners, Security, Infrastructure, and other stakeholders to deliver trusted data solutions.
• Mentor junior and mid-level engineers through pairing, code reviews, technical guidance, documentation, and knowledge sharing.
• Evaluate emerging technologies and recommend options that support Sentinel’s long-term data and engineering strategy.

Requirements

• Advanced SQL and strong programming experience with Python (or another data engineering language).
• Deep understanding of data modeling, data warehousing, data lakes, ETL/ELT, and workflow orchestration.
• Experience designing cloud-based solutions, preferably with AWS and its data services.
• Strong judgment balancing scalability, reliability, performance, security, delivery speed, and cost.
• A quality and reliability mindset, including ownership of data accuracy, lineage, monitoring, and operational readiness.
• Ability to communicate complex technical concepts clearly and build consensus across teams.
• Mentoring mindset and willingness to improve engineering practices across Sentinel.
• Curiosity about how AI can improve engineering productivity, data quality, testing, and operational support while protecting sensitive information.
• Commitment to building secure, maintainable, testable, observable, and cost-effective data systems.
• Demonstrated experience designing and operating production-grade data pipelines and data platforms.
• Demonstrated experience designing, building, deploying, and supporting production data pipelines.
• Advanced SQL including complex joins, transformations, performance tuning, and data validation.
• Strong programming experience with Python (or another language used for data processing and automation).
• Strong understanding of data modeling, relational databases, analytical warehouses, data lakes, and dimensional modeling.
• Experience with AWS or another major cloud platform, including cloud storage, compute, networking, monitoring, and access-control concepts.
• Experience implementing data quality checks, automated testing, observability, logging, alerting, and operational runbooks.
• Experience with Git, pull requests, CI/CD, infrastructure as code, and modern software development practices.
• Experience working with sensitive, confidential, regulated, or financial data and applying appropriate security controls.
• Ability to work in a hybrid environment, with one day in the office.
• Authorized to work in the US without current or future sponsorship.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, or a related field, or equivalent experience.
• 4+ years of professional experience in data engineering, data platform engineering, software engineering, or a related role.

Technologies

• SQL
• Python
• AWS
• Git
• CI/CD
• Infrastructure as code
• ETL/ELT

Benefits

• PTO (vacation, sick, personal time bank)
• FTO (Flexible time off for vacation, sick and personal time) after 2 years of service
• 12 Paid Holidays (10 stated and 2 floating holidays)
• 2 Community Volunteer Days
• 5 Summer Half Days
• Medical, Dental, Vision
• Life Insurance
• LTD & STD
• Retirement Plan with 4% Employer Match
• Parental Leave

Nice to Have

• Experience with Snowflake or another modern data platform.
• Experience with streaming or event-driven systems.
• Experience with Docker, Kubernetes, Terraform, CloudFormation, or similar technologies.
• Experience leading data-platform migrations or replacing legacy ETL processes.
• Experience with data contracts, metadata management, data catalogs, and lineage platforms.
• Experience supporting machine-learning, AI, semantic-layer, or feature-engineering use cases.
• Cloud or data-engineering certifications.
• Experience participating in technical interviews and contributing to hiring decisions.

Role Details

Location: Wakefield, MA (hybrid, one day in the office)

Salary: USD 106,000 to 113,000 per year

Experience: 4+ years

Education: Bachelor’s or Master’s degree (or equivalent experience)