Senior Data Engineer

Workana

7d • Hybrid

About The Position

Workana is the largest remote work platform for talent in Latin America. Our division focuses on matching exceptional professionals with leading and innovative companies around the globe. Our client is a fast-growing life sciences and biotechnology company operating at the intersection of computational research, data platform engineering, and advanced analytics. They develop production-grade data systems designed to support complex scientific research, clinical trial analytics, and machine learning workloads. We are looking for an experienced Senior Data Engineer to join their engineering team and take technical ownership of their data platform architecture.

Requirements

• 5+ years of experience in data engineering, data platform engineering, or data-intensive software engineering.
• Advanced professional experience with Python and SQL.
• Strong experience designing and owning production-grade distributed data architectures.
• Solid understanding of ETL/ELT patterns, data modeling, orchestration, and data observability.
• Strong software engineering fundamentals, including testing, CI/CD, version control, and system design.
• Experience handling large, complex, and heterogeneous datasets in cloud environments.
• Ability to work independently, manage technical ambiguity, and take ownership of deliverables.

Nice To Haves

• Experience with cloud platforms (AWS, GCP, or Azure) and technologies like Spark, Databricks, Snowflake, or BigQuery.
• Experience with workflow orchestrators such as Apache Airflow, Dagster, or Prefect.
• Domain experience in life sciences, clinical trials, genomics, or drug discovery datasets.
• Exposure to data governance, lineage, or operating within regulated data environments.

Responsibilities

• Architect, build, and maintain production-grade data platforms and scalable ELT/ETL pipelines.
• Ingest, transform, and model complex structured and unstructured scientific and clinical datasets.
• Define data architecture patterns, engineering standards, and best practices across the team.
• Collaborate with scientists, ML engineers, and business stakeholders to turn domain needs into data solutions.
• Design data infrastructure that supports machine learning training, inference, and analytics workloads.
• Ensure data quality, lineage, reproducibility, security, and system observability.
• Optimize pipeline performance, architectural bottlenecks, and infrastructure cost efficiency.
• Participate in technical design discussions, code reviews, and architectural decision-making.

Benefits

• Competitive salary with travel expenses covered when travel is required.
• Flexible work arrangements (Hybrid in Indianapolis, IN, or Fully Remote within the U.S. East Coast with occasional travel).
• Dynamic career growth with innovative, high-impact enterprise projects.
• Long-term independent contractor agreement.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed