Senior Data Engineer

Talenzaa; Glendale (CA); On-site; USD 102,000 - 170,000; Full time

Job summary

Talenzaa seeks a Senior Data Engineer to join its Data Platform team in Glendale, CA. You will design scalable cloud-based data platforms and modern data pipelines, collaborating with data engineers, architects, PMs, and data scientists to support BI, analytics, and ML initiatives.

The role requires hands-on work with Databricks, Spark, Airflow MWAA, and AWS, along with governance and containerization. Onsite in Glendale with competitive benefits.

Qualifications

• 5+ years of data engineering experience building and operating large-scale data pipelines.
• Hands-on experience with Databricks and Apache Spark (batch and streaming).
• Strong SQL skills with performance tuning and optimization.

Responsibilities

• Design, write, test, and deploy data pipelines using PySpark, Scala, SQL, Python.
• Collaborate with stakeholders to translate requirements into scalable data platform solutions.
• Explain Spark architecture and pipeline behavior to diagnose issues and propose solutions.
• Provide solution architecture across AWS, Databricks, Kubernetes, and Airflow (MWAA).
• Manage Databricks governance (Unity Catalog, ACLs, lineage) and data privacy tooling.
• Build and maintain Kubernetes containers supporting data platform services.
• Monitor platform health, cost, and access, and document changes for governance.

Skills

Databricks experience

Advanced SQL

PySpark/Scala

Python

Airflow (MWAA)

AWS

Docker and Kubernetes

Education

Bachelor's Degree in Computer Science / Information Systems or related field

Tools

Databricks tooling (API/SDK/CLI)

Airflow MWAA

Docker

Kubernetes

Snowflake

Job description

Location: Glendale, CA (2-3 Days Onsite)

Employment Type: Full-Time

Experience: 9–13 Years

Salary: Up to $170K + Benefits

Visa: USC, GC, GC-EAD. H4, L2 are preferred

LinkedIn is Must

Interview Process

• Expected to follow the team's recent hiring process for similar data engineering positions.
• Typically consists of:
  • Technical interview
  • Final interview (potentially onsite)
• Total process generally spans 2-3 interview rounds.

Job Overview

We are seeking an experienced Senior Data Engineer to join its growing Data Platform team. The ideal candidate will have strong expertise in designing and developing scalable cloud-based data platforms, modern data pipelines, and enterprise data models. You will work closely with data engineers, architects, product managers, and data scientists to build high-performance data solutions that support business intelligence, analytics, and machine learning initiatives. This role requires hands‑on experience with modern cloud technologies, data orchestration frameworks, and best practices in data governance.

Mandatory skills –

• Databricks experience (primary requirement)
• Advanced SQL skills
• Experience building and maintaining data pipelines and workflows

Key Responsibilities:

• Design, write, test, and deploy data pipelines using PySpark, Scala, SQL, Python
• Meet with stakeholders to gather requirements and translate them into scalable data platform solutions
• Understanding of Databricks platform and developer tooling to diagnose errors, audit platform activity, and automate updates across pipelines, objects, and integrations
• Ability to explain Spark architecture and pipeline behavior to stakeholders to diagnose root causes and recommend solutions
• Provide solution architecture across AWS, Databricks, Kubernetes, and Airflow (MWAA), including cross-platform integrations
• Manage Databricks platform governance, including Unity Catalog, ACLs, lineage, and data discovery and privacy tooling
• Build and maintain Kubernetes containers and containerized utilities supporting deployed data platform services
• Apply networking knowledge to troubleshoot connectivity and integration errors across platform components
• Perform platform administration: provision and remove access, assess resource utilization, monitor platform health and cost, and evaluate stakeholder requests
• Collaborate with engineers, architects, and product managers to drive Core Data platform success; participate in agile/scrum ceremonies
• Maintain documentation of platform changes, standards, and pipeline configurations to support data quality and governance

Qualifications:

• 5+ 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