Senior Data Engineer

Workana LLC; United States; Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive salary

Travel expenses covered when travel is

Flexible work arrangements

Long-term contractor agreement

Job summary

Workana LLC is seeking a Senior Data Engineer to own end-to-end data platform architecture, pipelines, and data modeling for science, analytics, and ML workloads. You will collaborate with researchers, engineers, and stakeholders to translate domain requirements into scalable solutions in a remote-friendly environment.

The role emphasizes autonomous ownership, best-practice data engineering, and cost-efficient infrastructure across cloud platforms, with opportunities to influence design

Qualifications

• 5+ years of data engineering experience or data platform engineering.
• Advanced Python and SQL proficiency.
• Experience designing production-grade distributed data architectures.
• Strong ETL/ELT, data modeling, orchestration, and observability.
• Solid software engineering fundamentals: testing, CI/CD, VCS, and system design.

Responsibilities

• Architect, build, and maintain production-grade data platforms and pipelines.
• Ingest, transform, and model complex datasets for analytics and ML workloads.
• Define data architecture patterns, standards, and best practices across the team.
• Collaborate with scientists, ML engineers, and stakeholders to translate needs into data solutions.
• Design data infrastructure supporting ML training, inference, and analytics.

Skills

Python

SQL

Data architectures

ETL/ELT

CI/CD

Cloud environments

Independent work

Tools

Spark

Databricks

Snowflake

BigQuery

Airflow

Dagster

Prefect

Job description

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.

About the client

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.

Role overview

As a Senior Data Engineer, you will own the end-to-end architecture, design, and implementation of scalable data platforms and processing pipelines. You will work directly with scientists, researchers, and machine learning engineers to translate complex domain requirements into technical solutions that power downstream analytics and production ML systems.

We are looking for a senior technical owner who can operate autonomously, drive best practices across distributed processing and data modeling, and collaborate effectively with international stakeholders in an English-speaking environment.

Selection process

The process usually consists of 4 stages and takes on average 4 weeks to be completed, depending on eventual additional technical rounds or take-home tests.

• Initial interview with Workana’s recruiting team;
• Technical interview with Workana’s technical team;
• Client Cultural fit interview;
• Final interview with C-level.

As Workana has multiple clients, if you pass the first round with Workana’s recruiting team, you may also be considered for other relevant opportunities if the initial opportunity does not move forward.

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.

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.

Bonus points

• 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.

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.