Databricks Data Engineer

Datavail Corporation
United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Airflow Amazon Web Services Microsoft Azure Big Data Cloud Computing Cluster Analysis Program Optimization Code Review Data Architecture Data Validation Data Governance
+28 more
Extract Transform Load (ETL) Data Migration Data Systems Software Debugging Apache Hive Python (Programming Language) Systems Development Life Cycle Standard Sql Data Streaming Transaction Data Google Cloud Snowflake Apache Spark Git Data Layers Data Lakes Pyspark Git Flow Information Technology Apache Kafka Spark Streaming Machine Learning Operations Terraform Stream Analytics Software Version Control Data Pipelines Legacy Systems Databricks

Job description

  • As a Databricks Data Engineer, you will work directly with clients across multiple industries to design, implement, and optimize Databricks-based data solutions
  • You will be a key member of our Professional Services delivery teams, delivering high-quality projects on time and within scope while building strong client relationships
  • This is a client-facing role that combines hands-on technical delivery with consulting best practices Key Responsibilities

  • Lead and contribute to end-to-end Databricks implementations for clients, including data migration, Lakehouse architecture, and pipeline development
  • Gather technical requirements, design solutions, and present recommendations to client stakeholders (technical and business)
  • Build scalable ETL/ELT pipelines using PySpark, Delta Lake, Delta Live Tables (DLT), and Databricks Workflows
  • Design and implement Databricks Genie
  • Design and implement semantic layers
  • Use Databricks AI features to accelerate development, debugging, and code optimization
  • Design and implement Lakebase architectures for operational and analytical workloads, including transactional data use cases
  • Develop solutions using SDLC best practices, including modular code design, testing, and documentation
  • Use Git based version control with proper branching strategies
  • Implement CI/CD pipelines for Databricks asset
  • Implement data quality checks, validations, and expectations within workflows
  • Design and implement Unity Catalog governance, security, and lineage solutions
  • Optimize Databricks workloads for performance, cost, and reliability (Photon, cluster policies, Liquid Clustering, Auto Loader, etc.)
  • Integrate Databricks with client ecosystems (Azure, AWS, GCP, Snowflake, Kafka, legacy systems, etc.)
  • Support client workshops, proof-of-concepts (POCs), and knowledge transfer sessions
  • Collaborate with client data teams to ensure successful adoption and handover of solutions
  • Deliver projects following consulting methodologies while meeting quality, timeline, and budget expectations
  • Document architectures, runbooks, and best practices for client use
  • Participate in solutioning activities (scoping, estimation, technical demos) as needed

Requirements

Do you have experience in Version control?, * 3 -5 years of hands-on Databricks experience (or strong Spark experience with significant recent Databricks work)

  • Proven experience delivering Databricks projects in a consulting or professional services environment (preferred) or equivalent client-facing project delivery
  • Strong proficiency in PySpark, Spark SQL, Python, and SQL
  • Deep experience with Delta Lake, Unity Catalog, Delta Live Tables, and Databricks Jobs
  • Hands-on experience with Git version control, pull requests, code reviews, and collaborative development workflows
  • Cloud platform experience (Azure Databricks, AWS, or GCP - at least one)
  • Excellent client-facing and communication skills - able to explain complex concepts to both technical and non-technical audiences
  • Solid understanding of data governance, security, and Lakehouse best practices
  • Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience) Nice-to-Haves

  • Databricks certifications (Data Engineer Associate / Professional, Lakehouse, etc.)
  • Experience with dbt, Airflow, Terraform, Databricks Asset Bundles (DABs), or MLflow
  • Background in specific industries (Financial Services, Healthcare, Retail, Manufacturing, etc.)
  • Experience with large-scale data migrations or legacy system modernization
  • Knowledge of streaming (Spark Structured Streaming / Kafka) and real-time analytics Skills & Qualities

  • Strong consulting mindset: ownership, adaptability, and client success focus
  • Excellent problem-solving, analytical, and presentation skills
  • Ability to work independently and as part of a delivery team
  • High emotional intelligence and stakeholder management ability
  • Commitment to delivering exceptional client outcomes

About the company

Datavail is one of the largest data focused services company in North America and provides both professional and managed services and expertise in Database Management, Application Development and Management, Cloud & Infrastructure Management, Packaged Applications and BI/Analytics

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