Data EngineerLocation: Ridgefield, Connecticut, United States
Work Arrangement: Flexible work-from-home days (onsite 2-3x per week)
Openings: 2
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.
Key Responsibilities:- 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.
Requirements:Data Engineer:- 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 DevOps/CI/CD principles and project lifecycle methodologies.
- Moderate knowledge of cloud platforms (AWS, Azure, GCP) and data integration concepts.
Senior Data Engineer:- 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/NoSQL databases.
- Hands-on experience with ETL/ELT tools (Airflow, dbt, AWS Glue).
- Knowledge of DevOps/CI/CD for data solutions.
Desired Skills & Abilities:- 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.
Technical Skills (Required):- AWS services: Glue, Lambda, Athena, Step Functions, Lake Formation
- Programming Languages: Python, SQL
