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Senior Data Engineer

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Hybrid

Senior Data Engineer

Tavant Technologies

Senior Data Engineer

Skills

SQL QueriesKotlinData EngineeringDockerPythonSnowflakeDatabricksScalaAWSKubernetesPySparkApache Airflow

21 days ago

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Important information


Contract type:

Permanent, Temporary

Salary:

$142,277 – $171,345 / year

Location:

Glendale, CA, USA

Work mode:

Hybrid

Published on:

30 September 2026

What they need


Must be willing to work Hybrid from Glendale, CA

We are not able to process Visa applicants for this role.

Job Summary

We are seeking a dynamic and highly skilled Senior Data Engineer to join our innovative data team. In this pivotal role, you will lead the development and optimization of large-scale data systems, ensuring seamless data flow, integrity, and accessibility across multiple platforms. Your expertise will drive strategic insights by designing robust data models, building scalable ETL pipelines, and leveraging cutting-edge cloud technologies. This position offers an exciting opportunity to influence data-driven decision-making processes and contribute to the evolution of our enterprise data architecture.

Responsibilities

  • 8+ years of data engineering experience developing and operating large-scale data pipelines
  • Deep hands-on experience with Databricks and Apache Spark (batch and streaming), including pipeline development in PySpark and/or Scala
  • Strong understanding of Spark architecture—executors, stages, partitioning, shuffle, and performance tuning—with ability to explain tradeoffs to technical and non-technical stakeholders
  • Proficiency with Databricks platform tooling (API, SDK, CLI) for automation, auditing, governance, and operational troubleshooting
  • Proficient in SQL with advanced performance tuning capabilities
  • Hands-on production experience with Airflow (MWAA) for orchestrating data pipelines
  • Experience managing Databricks platform governance: ACLs, Unity Catalog, lineage, and access provisioning
  • Proficiency in Python and at least one additional language (Scala, Kotlin, or SQL-driven pipeline tooling)
  • Experience designing and optimizing scalable ETL/ELT pipelines integrating diverse structured and unstructured data sources
  • AWS-primary experience (compute, storage, networking, IAM); experience with other cloud providers is transferable
  • Proficiency with Docker and Kubernetes for building and maintaining containerized data platform services
  • Working knowledge of networking concepts to diagnose cross-platform integration and connectivity issues
  • Familiarity with Snowflake and comparable tooling relative to the Databricks ecosystem
  • Experience designing and implementing CI/CD and DevOps practices (Git-based workflows)
  • Experience implementing data quality checks, monitoring, and logging for pipeline reliability
  • Self-starting problem solver with strong analytical and communication skills; willingness to learn new tooling and trends
  • Familiar with Scrum and Agile methodologies
  • Experience with Snowflake is a plus
  • Bachelor’s Degree in Computer Science, Information Systems, or a related field, or equivalent work experience, Master’s Degree is a plus

Pay: $142,277.97 - $171,345.52 per year

Benefits:

  • 401(k)
  • Dental insurance
  • Flexible schedule
  • Parental leave

Work Location: Hybrid remote in Glendale, CA 91201

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