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) About BigRio 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. Role Overview 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

Created: 2026-03-04