Data Engineer

Sentinel Group•Wakefield, MA

7d•$106,000 - $113,000•Hybrid

About The Position

The Data Engineer is part of the development team responsible for building, maintaining, enhancing, and integrating Sentinel’s data pipelines, data platforms, and connected systems. This role owns the design and delivery of secure, scalable, reliable, and well-documented data solutions that support Sentinel’s applications, reporting, analytics, and business decisions. A Data Engineer works across the full data engineering lifecycle: understanding business and technical requirements, defining architecture, documenting technical specifications, designing data models, developing and reviewing code, validating data quality, troubleshooting production issues, and supporting releases. This role provides technical leadership, makes sound engineering decisions, improves our standards and processes, and mentors other engineers while remaining hands-on in the work.

Requirements

A strong commitment to building secure, maintainable, testable, observable, and cost-effective data systems.
Demonstrated expertise designing and operating production-grade data pipelines and data platforms.
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 when balancing scalability, reliability, performance, security, delivery speed, and cost.
A quality and reliability mindset, including ownership of data accuracy, lineage, monitoring, and operational readiness.
The ability to communicate complex technical concepts clearly and build consensus across teams.
A mentoring mindset and willingness to improve engineering practices across Sentinel.
Curiosity about how AI can responsibly improve engineering productivity, data quality, testing, and operational support while protecting sensitive information.
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.
Demonstrated experience designing, building, deploying, and supporting production data pipelines.
Advanced SQL skills, 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 work environment, with one day in the office.
Authorized to work in the US without current or future sponsorship.

Nice To Haves

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.

Responsibilities

Lead the design, development, and evolution of end-to-end data pipelines, integrations, data models, and platform capabilities.
Own production data systems and contribute to their availability, monitoring, incident response, root-cause analysis, and continuous improvement.
Develop and own a long term vision for our data landscape.
Translate 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 identify risks and improve maintainability and performance.
Lead the modernization of legacy data processes and help move them toward secure, automated, cloud-based solutions that follow our CI.
Diagnose complex data, pipeline, performance, and reliability issues and drive both 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 make recommendations that support Sentinel’s long-term data and engineering strategy.

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