Data Engineer
Skills
- Strong programming in Python; familiarity with Java or Scala
- Experience with distributed data processing frameworks (Spark, Hadoop)
- Advanced SQL and data modeling skills
- Experience with cloud data platforms (AWS, Azure, GCP) and services (S3, Redshift, BigQuery)
- Hands-on ETL/orchestration tools (Apache Airflow, Informatica, Talend)
- Knowledge of relational and NoSQL databases and data warehousing concepts
- Familiarity with data governance, data quality, and security principles
- Experience with AWS CloudFormation and DMS
- Understanding of SDLC and agile delivery
- Exposure to computer vision / intelligent document processing (IDP) is a plus
Responsibilities
- Design and implement end-to-end data architectures (databases, warehouses, lakes, and large-scale processing systems).
- Build, test, and maintain scalable ETL/ELT pipelines to ingest and transform data from diverse sources.
- Optimize data retrieval, storage, and processing for performance, scalability, and cost efficiency.
- Collaborate with data scientists, analysts, and engineering teams to translate business requirements into technical solutions.
- Ensure compliance with data governance, security, and regulatory requirements.
- Automate data workflows and improve self-service data access for stakeholders.
- Develop dashboards, reports, and perform ongoing database maintenance and tuning.
- Create proofs of concept, predictive models, and high-performance algorithms as needed.
Education
- Bachelor’s degree in Computer Science, Engineering, or related field (required)
- Master’s degree in a related field (preferred)
Benefits
- Medical, dental, and vision insurance
- Short-term and long-term disability, plus life insurance
- 401(k) with company match
- Paid time off (120 hours PTO accruing over one year)
- Paid major holidays (14 days/year)
- Remote work environment and professional development opportunities
Average salary estimate
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