Data Engineer

Location: Ridgefield, Connecticut, United States

Work Arrangement: Flexible work-from-home days (onsite 2-3x per week)

Openings: 2

Step into the future with our Enterprise Data, AI & Platforms (EDP) team! At our company, we harness Data & AI to transform healthcare
, positively impacting the lives of millions of patients and animals. As part of the EDP team, you will contribute to building a strong data-driven culture
, drive key data transformation initiatives
, and shape the future of decision-making across our global organization.

We are seeking a highly skilled and experienced Data Engineer to design, build, and maintain scalable data infrastructure on a cloud platform. You will be responsible for data pipelines, ETL processes, and overall data architecture strategy
, ensuring data availability, quality, and integrity for business stakeholders and analytics teams.

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Collaborate with data architects, modelers, IT, and business stakeholders to define and evolve cloud-based data architecture.
• Optimize data storage solutions (e.g., S3, Snowflake, Redshift), ensuring data integrity, security, and accessibility.
• Implement data quality, validation processes, and monitoring frameworks.
• Maintain documentation for data workflows, architecture, and pipeline processes.
• Troubleshoot and optimize data pipeline performance.
• Engage with clients and stakeholders to analyze requirements and recommend data solutions.
• Stay current with emerging technologies and industry trends in cloud and data engineering.

• Associate degree in Computer Science/MIS (4+ years experience) or Bachelor's (2+ years) or Master's (1+ year) in related field.
• Hands‑on experience with AWS services (Glue, Lambda, Athena, Step Functions, Lake Formation).
• Proficiency in Python and SQL.
• Familiarity with Dev Ops/CI/CD principles and project lifecycle methodologies.
• Moderate knowledge of cloud platforms (AWS, Azure, GCP) and data integration concepts.

• Associate degree (8+ years experience) or Bachelor's (4+ years) or Master's (2+ years) in relevant field.
• Expert‑level experience in cloud platforms, preferably AWS.
• Advanced SQL skills, data modeling, and data warehousing concepts (Kimball, star/snowflake schemas).
• Experience with big data frameworks (Spark, Hadoop, Flink) and relational/No
  
  SQL databases.
• Hands‑on experience with ETL/ELT tools (Airflow, dbt, AWS Glue).
• Knowledge of Dev Ops/CI/CD for data solutions.

• 4+ years of progressive data engineering experience with cloud-based data platforms.
• Understanding of data governance, data quality, and metadata management.
• Familiarity with Snowflake and dbt (data build tool).
• Strong problem‑solving skills in pipeline troubleshooting and optimization.
• AWS Solutions Architect certification is a plus.

• AWS services:
  Glue, Lambda, Athena, Step Functions, Lake Formation
• Programming
  
  Languages:
  
  Python, SQL