Data Pipeline Engineer

Data Pipeline Engineer

Location: Remote (US / India / Global – based on project needs) Employment Type: Contract / Full-Time Industry: Healthcare, Life Sciences, Data & AI Experience: 5–10+ years (flexible based on strength)

BigRio is a trusted data, analytics, AI, and cloud consulting partner specializing in healthcare and life sciences. We help organizations modernize data platforms, build scalable pipelines, and unlock insights through cloud-native and AI-driven solutions. Our teams work on high-impact, real-world problems involving healthcare data, compliance, and advanced analytics.

We are seeking a Data Pipeline Engineer to design, build, and maintain scalable, reliable, and secure data pipelines supporting analytics, reporting, and AI/ML initiatives. This role focuses on ingesting, transforming, and delivering high-quality data across cloud platforms, with a strong emphasis on healthcare and regulated data environments.

Key Responsibilities:

• Design, develop, and maintain end-to-end data pipelines (batch and streaming) for structured and unstructured data
• Build robust ETL / ELT workflows to ingest data from multiple sources including APIs, databases, files, and third-party systems
• Implement data transformations, validations, and quality checks to ensure accuracy and reliability
• Optimize pipeline performance, scalability, and cost efficiency
• Work closely with data analysts, BI engineers, data scientists, and product teams to support downstream analytics and AI use cases
• Ensure data pipelines comply with security, privacy, and HIPAA requirements where applicable
• Monitor pipelines, troubleshoot failures, and implement alerting and recovery mechanisms
• Contribute to data architecture decisions, documentation, and best practices

Required Qualifications:

• 5+ years of experience building and supporting data pipelines in production environments
• Strong experience with SQL and data modeling concepts
• Hands-on experience with ETL/ELT frameworks and orchestration tools
• Experience working with cloud platforms (Azure, AWS, or GCP)
• Proficiency with data processing tools such as Azure Data Factory, Databricks, Spark, Airflow, or similar
• Experience integrating data from APIs, flat files, relational databases, and cloud storage
• Strong understanding of data quality, lineage, and pipeline reliability
• Excellent problem-solving and communication skill

Nice to Have:

• Healthcare domain experience (provider, payer, clinical, claims, PHI data)
• Experience with streaming data (Kafka, Event Hub, Kinesis, etc.)
• Exposure to Snowflake, BigQuery, Redshift, or other cloud data warehouses
• Familiarity with Python or Scala for data processing
• Experience supporting BI tools (Power BI, Tableau, Looker)
• Knowledge of CI/CD, DevOps, and Infrastructure-as-Code