Senior Data Engineer, Operations (USA)

Gigster

Austin (TX)

On-site

Full time

14 days+

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Benefits offered by this job

Stable, long-term independent contract agreement

Remote work within the contiguous United States

Full-time hours

Job summary

A tech consulting firm is looking for a Senior Data Engineer to manage and optimize production data pipelines. This role involves debugging, triaging, and operational support of ingestion and transformation processes. Strong programming skills in Python and SQL are essential, along with experience in CI/CD practices. This is a fully remote, full-time position within the contiguous United States, offering an independent contract agreement. If you're eager for a fast-paced environment with growth opportunities, apply now.

Qualifications

7+ years of experience in data engineering, analytics engineering, or software development.
Experience in operating and supporting production data pipelines.
Hands-on experience with CI/CD and Docker.

Responsibilities

Build and maintain automation, scripts, and tooling to support operational workflows.
Own operational support for ingestion and transformation pipelines.
Monitor pipeline health, data freshness, and quality metrics.

Skills

Strong programming skills in Python

Strong programming skills in SQL

Data pipeline support

Debugging and triaging

Experience with streaming and distributed compute

Tools

Airflow

Spark

dbt

Kafka

Snowflake

Job description

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Virtasant is a global technology services company with a network of over 4,000 technology professionals across 130+ countries. We specialize in cloud architecture, infrastructure, migration, and optimization, helping enterprises scale efficiently while maintaining cost control.

Our clients range from Fortune 500 companies to fast-growing startups, relying on us to build high-performance infrastructure, optimize cloud environments, and enable continuous delivery at scale.

About the Role

We're seeking a Senior Data Engineer - Operations to support our data platform, with a strong focus on triaging, debugging, and operating production data pipelines. This role sits within the Data Platform Operations pillar and is responsible for the day-to-day health, reliability, and correctness of ingestion pipelines, transformations, and analytics workflows.

You’ll work hands‑on across ingestion, orchestration, dbt transformations, and medallion‑layer data models, partnering closely with other data and analytic engineers and DevOps to ensure timely resolution of data issues and smooth platform operations.

What You’ll Do

Build and maintain automation, scripts, and lightweight tooling to support operational workflows, including pipeline triage, data validation, backfills, reprocessing, and quality checks. Improve self‑service and reduce manual operational toil.
Own operational support for ingestion and transformation pipelines built on Airflow, Spark, dbt, Kafka, Snowflake (or similar). Triaging failed jobs, diagnosing data issues, performing backfills, and coordinating fixes across ingestion, transformation, and analytics layers.
Monitor pipeline health, data freshness, and quality metrics across medallion layers. Investigate data anomalies, schema drift, and transformation failures, and drive incidents to resolution through root‑cause analysis and corrective actions.
Act as the primary interface between Data Platform, Analytics Engineering, and downstream consumers during operational issues. Communicate impact, coordinate fixes, and ensure timely resolution of data incidents.

What We’re Looking For

Must live in the contiguous United States and have all necessary documentation to work under an independent contractor agreement. Cannot offer sponsorships or sponsorship transfers; H1B, OPT, EAD, or CPT visas are not considered.
7+ years of experience in data engineering, analytics engineering, or software development, with significant experience operating and supporting production data pipelines.
Strong programming skills in Python & SQL on at least one major data platform (Snowflake, BigQuery, Redshift, or similar).
Experience supporting schema evolution, data contracts, and downstream consumers in production environments.
Strong experience triaging, debugging, and maintaining dbt models, including understanding dependencies across medallion layers (bronze/silver/gold).
Experience with streaming, distributed compute, or S3‑based table formats (Spark, Kafka, Iceberg/Delta/Hudi).
Experience with schema governance, metadata systems, and data quality frameworks.
Hands‑on experience operating and debugging orchestration workflows (Airflow, Dagster, Prefect), including retries, backfills, and dependency management.
Solid grasp of CI/CD, Docker, and at least 2 years of experience in AWS.

Preferred / Nice‑to‑haves

Experience participating in on‑call rotations, incident response, or data operations teams.
Experience with data observability, data catalog, or metadata management tools.
Experience working with healthcare data (X12, FHIR).
Understanding of authentication/authorization (OAuth2, JWT, SSO).

Why This Role is Exciting

This is a very fast‑paced, high‑pressure role, where you can learn a lot. If this makes your eyes spark, then please apply! If you can build tenure in this role, the potential is endless. You'll be an SME in many key areas for our client, and you'll work with Analytics Engineers and with downstream reporting tools.

Our Recruitment Process

Technical Interview (45 min)
Screening interview with the client's hiring manager (30 min)
Client technical interview (45 min)
We strive to move efficiently from step to step so that the recruitment process can be as fast as possible.

What We Offer