Data Pipeline Engineer in , United States

Energy Jobline
United States
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Airflow Amazon Web Services Microsoft Azure BigQuery Cloud Computing Cloud Database Cloud Storage Databases Continuous Integration Data Architecture
+24 more
Data Infrastructure Data Integration Extract Transform Load (ETL) Data Transformation Data Security Relational Databases DevOps Python (Programming Language) Power BI SQL Databases Data Streaming Tableau (Software) Unstructured Data Workflow Management Systems Data Processing Azure Data Factory Snowflake Apache Spark Apache Kafka Data Management Looker Analytics Data Pipelines Amazon Redshift Databricks

Job description

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- 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., 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

Requirements

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

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