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Data Engineer

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An innovative and fast-growing consultancy in Boston, MA is seeking a Data Engineer to join their dynamic team. In this role, you'll design, build, and maintain cutting-edge data infrastructure that powers insights and drives decision-making. If you’re passionate about data engineering, cloud technologies, and want to work on impactful projects in the healthcare and technology sectors, this role is perfect for you.

Role:

πŸ› οΈ Design, build, and manage scalable data lakes and data warehouses.

πŸ“Š Develop robust, automated ETL/ELT pipelines to ingest and transform large datasets.

πŸ” Build dynamic, metadata-driven pipelines to handle billions of data rows efficiently.

☁️ Work with cloud platforms like Azure, AWS, or GCP to optimize data solutions.

πŸ“ˆ Enable advanced analytics by creating high-quality datasets for reporting and modeling.

🀝 Collaborate with cross-functional teams to deliver innovative data-driven solutions.

Requirements:

πŸŽ“ 2–4 years of hands-on experience in data engineering or related roles.

🐍 Proficiency in Python and advanced SQL for data manipulation.

πŸ—οΈ Expertise in building data pipelines and managing big data architectures.

🌐 Cloud experience in Azure, AWS, or GCP.

⚑ Experience with ETL/ELT pipelines, data modeling, and warehouse optimization.

πŸ’‘ Bonus: Knowledge of Spark/PySpark, Power BI/Tableau, and data modeling techniques (Kimball, Star/Snowflake schemas).

βœ… Relevant cloud certifications are a plus.

Benefits:

πŸ’΅ Salary Range: $80,000 – $100,000 per year

πŸ₯ Group medical, dental, and vision insurance

πŸ’° 401(k) savings plan with company contributions

πŸ–οΈ 15 paid vacation days + 10 sick days + 10 paid holidays

πŸŽ“ Professional development & certification support

🏒 Hybrid work model β€” minimum 2 days in the office

🐾 Pet, legal, and voluntary insurance options

🎯 Annual performance-based bonuses

Skills:

Data Engineering, Big Data, ETL, ELT, Python, SQL, Spark, PySpark, Data Lakes, Data Warehouses, Cloud Computing, Azure, AWS, GCP, Data Modeling, Power BI, Tableau, Analytics, Automation, Pipelines, Metadata