Databricks Developer
- Status
- Open
- Remote policy
- Remote
- Employment type
- Not stated
- Salary
- Not stated
- Categories
- Data-Engineering, Databricks-Developer, Big-Data-Developer, PySpark-Developer, Data-Pipeline-Engineer, Azure-Databricks-Developer, Databricks-Development, Databricks-Engineer, Databricks-Specialist, Databricks-Data-Engineer, Developer
- Source
- himalayas
- First observed
- 2026-08-21 18:10 UTC
- Last seen
- 2026-08-21 18:10 UTC
- Source claims posted
- 2026-08-21 17:53 UTC
- Consecutive misses
- 0 of 10
What the posting says
Trinetix is looking for a skilled Databricks Developer with strong expertise in Apache Spark, Python, and modern data engineering practices. This role involves designing, developing, and maintaining scalable data ingestion, transformation, and analytics pipelines using Databricks and related technologies. The ideal candidate is analytical, detail-oriented, and experienced in working with large-scale data, performance optimization, and reliable data processing solutions.
Requirements
5+ years of hands-on software development experience
Strong expertise in Apache Spark, including hands-on experience delivering solutions on Databricks
Advanced Python and data engineering skills, including strong experience with PySpark, Pandas, and related libraries
Experience developing and maintaining unit tests for Databricks workloads
Solid understanding of columnar storage formats, such as Parquet
Hands-on experience with Delta Lake and Delta Tables
Proven experience working with small to large data volumes, including performance tuning and optimization
Experience building data ingestion, transformation, and analytics pipelines
Hands-on experience with Databricks Workflows
Strong analytical and problem-solving skills with close attention to detail
Conversational English — B2 level or higher
Conversational Ukrainian
Nice-to-haves
Familiarity with Databricks DevOps practices
Experience with CI/CD processes for data engineering workloads
Understanding of software development lifecycle and engineering best practices
Experience working with distributed data processing environments
Experience working in cross-functional, distributed teams
Familiarity with enterprise-level data platforms and large-scale data environments
Core Responsibilities
Design, develop, and maintain scalable data ingestion, transformation, and analytics pipelines using Databricks
Develop data processing solutions using Apache Spark and PySpark
Work with large-scale datasets and implement performance tuning and optimization strategies
Design and maintain Delta Lake / Delta Table solutions to support reliable and scalable data processing
Develop and maintain unit tests to ensure the quality and reliability of Databricks workloads
Implement and manage Databricks Workflows for data processing and pipeline orchestration
Work with columnar storage formats such as Parquet and optimize data processing and storage solutions
Analyze business and technical requirements and translate them into effective data engineering solutions
Collaborate with cross-functional teams to ensure data pipelines and solutions meet technical and business requirements
Apply data engineering and software development best practices to deliver maintainable, scalable, and reliable solutions
About Us
Established in 2011, Trinetix is a dynamic tech service provider supporting enterprise clients around the world.
Headquartered in Nashville, Tennessee, we have a global team of over 1,000 professionals and delivery centers across Europe, the United States, and Argentina. We partner with leading global brands, delivering innovative digital solutions across Fintech, Professional Services, Logistics, Healthcare, and Agriculture.
Our operations are driven by a strong business vision, a people-first culture, and a commitment to responsible growth. We actively give back to the community through various CSR activities and adhere to international principles for sustainable development and business ethics.
To learn more about how we collect, process, and store your personal data, please review our Privacy Notice:
Requirements
Originally posted on Himalayas
Quality
- x Salary range stated weight 35%
- + Remote policy stated weight 20%
- + Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Not enough history yet to judge honesty signals.
Timeline
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#250438 2026-08-21 18:10 UTCPublished