Data Engineer

Sentinel Group is seeking a Data Engineer to design, build, and maintain secure, scalable data pipelines and platforms. The role covers end-to-end ownership across architecture, modeling, validation, troubleshooting, and production releases.

Key Responsibilities

• Lead the design, development, and ongoing evolution of end-to-end data pipelines, integrations, data models, and platform capabilities.
• Own production data systems, including availability, monitoring, incident response, root-cause analysis, and continuous improvement.
• Create and maintain a long-term vision for the data landscape.
• Convert business and technical requirements into clear architecture, implementation plans, and incremental deliverables.
• Design and implement scalable ETL/ELT workflows that ingest, transform, validate, and deliver data from APIs, databases, files, and other systems.
• Define and improve standards for data quality, testing, documentation, lineage, observability, security, governance, and access control.
• Review architecture, technical designs, pull requests, and operational changes to reduce risk and improve maintainability and performance.
• Modernize legacy data processes, supporting the transition to secure, automated, cloud-based solutions aligned with Sentinel’s CI.
• Diagnose complex issues across data, pipelines, performance, and reliability, driving immediate mitigation and durable prevention.
• Optimize queries, storage, processing, and infrastructure for 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.

Required Qualifications

• Advanced SQL skills and strong programming experience with Python or another language used for data engineering.
• Deep understanding of data modeling, data warehousing, data lakes, ETL/ELT, and workflow orchestration.
• Experience designing cloud-based solutions, preferably using AWS and its data services.
• Strong judgment balancing scalability, reliability, performance, security, delivery speed, and cost.
• A quality and reliability mindset focused on data accuracy, lineage, monitoring, and operational readiness.
• Ability to communicate complex technical concepts clearly and build consensus across teams.
• Mentoring mindset and willingness to strengthen engineering practices across Sentinel.
• Interest in how AI can responsibly 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 expertise designing and operating production-grade data pipelines and data platforms, including designing, building, deploying, and supporting production pipelines.
• Advanced SQL capabilities, including complex joins, transformations, performance tuning, and data validation.
• 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 while 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

Location and Compensation

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

Compensation: USD 106,000 - 113,000 per year.

Experience: 4+ years.

Benefits

• PTO (vacation, sick, personal time bank)
• FTO after 2 years of service (Flexible time off for vacation, sick and personal time)
• 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.