Mid-Level Databricks Engineer

Techstrasolutions

1h 8m ago

On-site

Full Time

United States of America

We are seeking a Mid-Level Databricks Engineer to design, develop, and support scalable data solutions using Databricks and modern cloud data platforms. This role will focus on building reliable data pipelines, implementing lakehouse architectures, improving data quality, and supporting analytics and AI use cases.

The ideal candidate has strong hands-on experience with Databricks, SQL, Python/PySpark, Delta Lake, and cloud data services and can work independently within established architectural and data governance standards.

Key Responsibilities

Design, build, test, and maintain data pipelines using Databricks, PySpark, Python, and SQL.
Develop ingestion and transformation processes across Bronze, Silver, and Gold layers using Medallion Architecture principles.
Build and optimize Delta Lake tables, including data partitioning, schema management, and performance tuning.
Develop batch and streaming pipelines using Databricks capabilities such as Auto Loader, Structured Streaming, Workflows, and Delta Live Tables/Lakeflow Declarative Pipelines, where appropriate.
Integrate structured and semi-structured data from databases, APIs, files, cloud storage, and enterprise applications.
Implement data quality validation, reconciliation, exception handling, monitoring, and logging.
Work with Unity Catalog to support data governance, access controls, metadata management, lineage, and data discovery.
Develop reusable frameworks and components for ingestion, transformation, and data validation.
Troubleshoot pipeline failures and performance issues and implement sustainable fixes.
Participate in code reviews and follow established development, testing, security, and deployment standards.
Support CI/CD practices for Databricks development and collaborate with DevOps teams on automated deployments.
Work closely with data architects, analysts, data scientists, governance teams, and business stakeholders.
Create and maintain technical documentation, data mappings, pipeline specifications, and operational support documentation.

Required Qualifications

8-10 years of experience in data engineering, ETL/ELT development, or related data platform development.
5+ years of hands-on Databricks experience preferred.
Strong proficiency with:
- Python / PySpark
- SQL
- Apache Spark
- Delta Lake
- Databricks notebooks, jobs/workflows, and compute
Experience developing scalable ETL/ELT pipelines and working with large datasets.
Understanding of lakehouse, data warehouse, and Medallion Architecture concepts.
Experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud.
Experience working with Git-based source control and CI/CD processes.
Understanding of data quality, metadata, lineage, security, and data governance concepts.
Strong troubleshooting, analytical, and problem-solving skills.
Ability to work effectively in an Agile delivery environment.

Preferred Qualifications

Experience with Databricks Unity Catalog.
Experience with Azure Data Lake Storage, Azure Data Factory, Azure DevOps, or comparable AWS/GCP services.
Experience with Databricks Asset Bundles and infrastructure/deployment automation.
Familiarity with REST APIs, JSON, Parquet, Avro, and other common data formats.
Exposure to Power BI
Experience supporting data science, machine learning, or GenAI workloads is a plus.
Databricks certification such as Databricks Certified Data Engineer Associate is a plus.

What We're Looking For

A successful candidate should be able to take a defined data requirement or technical design and independently turn it into a production-ready Databricks solution. They should be comfortable troubleshooting problems, collaborating with senior engineers and architects, and helping less-experienced developers follow good engineering practices.

Leveling distinction: This is not primarily an architecture role. The emphasis is on hands-on engineering, independent delivery, code quality, data reliability, and Level 2 production support.

Equal Employment Opportunity Statement

Techstra Solutions is an equal opportunity employer. The Company makes its decisions on merit, and its policy of equal opportunity prohibits discrimination in all phases of the employment process, including, but not limited to, recruitment, hiring, promotion, selection, transfer, demotion, layoff, termination, compensation, benefits, and other terms and conditions of employment. The policy of equal opportunity applies without regard to race, color, creed, religion, gender, sexual orientation, gender identification, pregnancy, marital status, national origin, ancestry, age, disability that can reasonably be accommodated without undue hardship, military status, veteran status, genetic predisposition or carrier status, alienage or citizenship, domestic partnership status, arrest or conviction record, status as a victim of domestic violence, or any other protected categories under federal, state, or local law. The Company also prohibits discrimination or harassment based upon the perception that a person has, or is associated with a person who has, any of these characteristics.
Candidate Data Privacy and Use:
Techstra Solutions respects the privacy of our candidates. By submitting your application, you acknowledge that Techstra Solutions may collect, store, and process the information you provide for recruiting, candidate evaluation, and consideration for current or future opportunities. Techstra may use applicant tracking systems, analytics, automation, and AI-assisted tools to support these activities. Candidate information will be protected using appropriate safeguards and retained or deleted in accordance with applicable law and Techstra’s data retention practices.

Required Skills

databrickspysparkpythonsqlsparkgit

Required Languages

🇬🇧 English