Job Description

Salary is 120k to 140k + bonus

We are seeking a skilled and motivated Data Engineer with strong Python experience and proficiency in ETL processes to join our growing data engineering team. This role will focus on designing, building, and optimizing scalable data pipelines and infrastructure that support data analytics, reporting, and machine learning initiatives.

Key Responsibilities:

• Design and develop robust, scalable, and reusable data pipelines using Python and ETL frameworks
• Build batch and streaming workflows to ingest, transform, and integrate data from a variety of structured and unstructured sources
• Collaborate with data analysts, scientists, and stakeholders to understand business needs and deliver reliable data solutions
• Develop and maintain data models, data mappings, and data validation processes
• Ensure high data quality, consistency, and availability across the data platform
• Automate and orchestrate workflows using scheduling and orchestration tools
• Monitor data pipelines for performance and reliability; troubleshoot issues and optimize processes

Tech Stack & Tools:

• Programming: Python (Pandas, PySpark, etc.), SQL
• ETL Tools (experience with at least one):
• Apache Airflow
• AWS Glue
• Talend
• Informatica
• Microsoft SSIS
• Apache NiFi
• Matillion
• Cloud Platforms: AWS, Azure, or GCP (S3, Redshift, BigQuery, Data Lake, etc.)
• Databases: PostgreSQL, MySQL, Snowflake, Redshift, MongoDB, etc.
• Data Storage & Formats: Parquet, Avro, JSON, Delta Lake
• DevOps: Git, Docker, CI/CD (GitLab CI, GitHub Actions)

Required Qualifications:

• 3+ years of experience as a Data Engineer or in a similar data-intensive role
• Strong Python skills for building and automating data pipelines
• Proficient in writing complex SQL queries and working with relational databases
• Experience with at least one ETL or orchestration platform (Airflow, Glue, etc.)
• Familiarity with cloud-native data infrastructure and data lake architecture
• Solid understanding of data modeling, warehousing, and pipeline performance tuning

Preferred Qualifications:

• Healthcare industry
• Exposure to big data tools (Spark, Kafka, Hive)
• Experience with infrastructure-as-code (Terraform, CloudFormation)
• Knowledge of data governance, privacy, and compliance standards
• Background working in agile and DevOps environments

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