Data Engineer
Remote · United States
Job Summary
Data Engineer to design, build, and maintain scalable data infrastructure and reliable data pipelines powering analytics, reporting, and operational decision-making. Responsibilities include building and optimizing ETL/ELT pipelines (Python/SQL/Scala), orchestrating workflows (Airflow/Prefect/Dagster), ingesting data from APIs, SaaS, databases, and streaming systems, and developing scalable connectors. Implement data warehousing and modeling in Snowflake/BigQuery/Redshift with star/snowflake schemas, partitioning, clustering, and performance optimization. Ensure data quality, governance, and reliability with validation, lineage, and documentation using tools like dbt and Great Expectations, plus GDPR/HIPAA compliance. Build real-time pipelines (Kafka/Kinesis/Pub/Sub), monitor pipeline health, and collaborate with analysts and data scientists to deliver curated datasets for BI tools (Tableau/Looker/Power BI). Leverage containerization (Docker), CI/CD (GitHub Actions/Jenkins/GitLab CI), and cloud infrastructure IaC (Terraform/CloudFormation). AEM-focused on delivering accurate, timely, and scalable data powering operational, analytical, and strategic decisions.
Required Qualifications
- 3+ years of experience in Data Engineering, Back-End Engineering, or Data Infrastructure roles
- Strong proficiency in Python and SQL
- Experience with at least one modern data warehouse (Snowflake, Redshift, BigQuery)
- Hands-on experience with orchestration tools such as Airflow or Prefect
- Strong understanding of ETL/ELT pipelines, data modeling, and data transformation workflows
- Familiarity with cloud platforms such as AWS, GCP, or Azure
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