Senior Data Engineer

About the Company This is a growing technology consulting firm focused on cloud, data, automation, and AI. The business works with clients on modernizing enterprise systems and solving complex data and technology challenges. Its data practice delivers architecture and engineering work across major cloud platforms, with a strong focus on modern data platforms and Databricks-based environments. The Role This Senior Data Engineer will take ownership of designing and delivering scalable data platforms for client environments. The role combines hands-on engineering with architecture, technical leadership, and client-facing work, so it suits someone who can move comfortably between building pipelines, making design decisions, and explaining those decisions to stakeholders. What You Will Do Design modern data platforms spanning lakehouse, warehouse, ingestion, transformation, and analytics workloads. Build and optimize batch and streaming pipelines using Databricks, Spark, Kafka, Delta Live Tables, and Autoloader. Turn business and analytics requirements into practical data models, integration patterns, and technical architectures. Lead data modernization and migration work, including moving traditional warehouse workloads onto Databricks-based platforms. Improve platform reliability, performance, governance, and security while providing technical guidance to engineers and clients. What You Bring 5+ years of experience across data engineering, data architecture, or analytics solution design, with strong SQL and Python, PySpark, or Scala skills. Hands-on experience with modern lake and warehouse technologies such as Databricks, Snowflake, Redshift, or Synapse, plus working knowledge of AWS or Azure. Strong Databricks experience, including Autoloader, Delta Live Tables, Medallion architecture, and large-scale ETL/ELT pipeline development. Experience building streaming ingestion with technologies such as Kafka and Spark Structured Streaming, alongside solid data modeling and integration fundamentals. Experience implementing CI/CD for Databricks workloads using tools such as Azure DevOps, GitHub Actions, or GitLab CI, with the communication skills to present technical solutions directly to clients. Why This Role The scope goes well beyond maintaining pipelines. You will work across architecture, migrations, streaming, cloud infrastructure, governance, and client advisory work, with direct involvement in how modern data platforms are designed and delivered.

Design and deliver scalable data platforms, including lakehouse and warehouse architectures, for various client environments. Build and optimize batch and streaming pipelines while providing technical leadership and advisory services to stakeholders.

Requires over 5 years of experience in data engineering or architecture with proficiency in SQL, Python, and Databricks. Candidates must have experience with streaming ingestion, CI/CD tools, and cloud platforms like AWS or Azure.

• Microsoft AzurePreferred
• SQLPreferred
• Amazon Web ServicesPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Databricks
• Apache Spark
• Python
• SQL
• PySpark
• Scala
• Kafka
• Delta Live Tables
• Azure DevOps
• GitHub Actions
• GitLab CI
• Data Modeling
• ETL/ELT
• AWS
• Azure
• Snowflake

• Data & Analytics
• Technology
• Consulting
• Engineering
• Software

Minimum experience

5+ years

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available