Sr Data Engineer

The Data Engineer is responsible for building, and operating scalable, secure, and high-performance data platforms that enable analytics, reporting, and AI initiatives. This role leads the development of modern (ETL/ELT) data solutions across Microsoft Fabric and Azure, ensuring enterprise-grade data integration, governance, and performance optimization.

Top Must-Haves:

Azure Data Engineering Expertise – 5+ years building production data solutions on Azure, with strong hands-on experience in Microsoft Fabric plus tools like Azure Data Factory, Synapse, Databricks, or Azure SQL.

Strong ETL/ELT & Data Architecture Skills – Proven ability to design scalable pipelines and modern data architectures (lakehouse/medallion) supporting structured and unstructured data.

Advanced Programming & Data Processing – High proficiency in SQL and Python, plus experience with Spark and data processing frameworks (Pandas, PyArrow, etc.).

CI/CD & Data Platform Engineering – Experience implementing CI/CD pipelines, Git workflows, automated deployments, and environment promotion for data platforms.

Security & Enterprise Data Controls – Hands-on experience with RBAC, Key Vault, managed identities, and implementing secure, governed data architectures.

Preferred Skills:

Microsoft Fabric Certifications – DP-700 (required/expected), plus DP-600 or DP-203.

Performance Optimization & Cost Efficiency – Experience with Delta storage, partitioning, columnstore optimization, and query performance tuning.

Integration & Hybrid Data Environments – Experience integrating APIs, third-party platforms, and hybrid (on-prem + cloud) systems.

Analytics & AI Data Enablement – Experience supporting downstream semantic models and partnering with analytics/AI teams.

High-Scale / Regulated Environments – Background working in enterprise, highly regulated, or large-scale data platforms.

Leadership & Collaboration – Ability to lead design decisions, mentor junior engineers, and collaborate across technical and business teams in Agile environments.

Title: Sr. Data Engineer

Location: Woburn, MA – ONSITE 5 days a week

Duration: 6 month contract

Job Details:

Develop and maintain scalable ETL (Extract, Transform, Load) processes to efficiently extract data from diverse sources, transform it as required and load it into data warehouses or analytical systems.

Design and optimize database architectures and data pipelines to ensure high performance, availability and security while supporting structured and unstructured data.

Build and maintain robust ETL/ELT pipelines using Fabric Pipelines, Azure Data Factory, and Synapse.

Implement secure data architectures using Roles-based Access Controls (RBAC), Key Vault, Private Endpoints

Integrate data from APIs, third-party platforms, and hybrid (on-prem/cloud) systems.

Develop data workflows using Python, SQL, and Spark, selecting appropriate frameworks based on workload characteristics.

Drive cost-efficient, low-latency analytics through partition-aligned Delta storage, columnstore-optimized warehouse tables, DirectLake semantic access, and SCD-managed dimensional models, ensuring predicate pushdown, partition elimination, and minimal data movement across the query execution lifecycle.

Implement secure data architectures using:

RBAC and row/column/object-level security (RLS/CLS/OLS)

Azure Key Vault, Private Endpoints, Managed Identities.

Implement CI/CD pipelines for data platforms using Azure DevOps or GitHub

Establish automated deployment, environment promotion, and testing strategies.

Support downstream semantic models and reporting layers by delivering well-modeled, performant, and governed data structures (no report/dashboard development responsibilities).

Partner with analytics and AI teams to deliver trusted, production-ready data products.

Ensure platform reliability through constraint-driven data validation, fault-tolerant pipeline orchestration, and telemetry-backed observability, enabling anomaly detection, automated alerting, and lineage-driven root cause analysis across distributed data workloads.

Lead design decisions and influence enterprise data architecture standards

Collaborate with engineers, analysts, and business stakeholders to translate requirements into scalable solutions.

Mentor junior engineers and contribute to engineering excellence and knowledge sharing.

Operate effectively in Agile delivery environments.

Required Qualifications

8+ years of experience in data, software, or platform engineering.

5+ years building production data solutions on the Microsoft/Azure stack.

Strong experience with Microsoft Fabric and at least two of:

Azure Data Factory, Synapse, Databricks, Azure SQL, Power BI

Advanced proficiency in SQL and Python (delta-rs, PyArrow, Polars, DuckDB, Pandas, and NumPy).

Proven experience designing modern data architectures (lakehouse, medallion, etc.).

Hands-on experience with CI/CD, Git workflows, and environment promotion.

Experience implementing enterprise security, identity, and access controls.

Strong troubleshooting, performance tuning, and root cause analysis skills.

Experience working in regulated or high-scale environments.

Preferred Qualifications

• Certifications:

• DP-700 (Fabric Data Engineer) – required or within 6 months.

• DP-600,DP-203– preferred.