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We are seeking an experienced, hands-on Data Analyst – Databricks to help build, optimize, and enhance our modern data and analytics environment. The successful candidate will bring a strong combination of Databricks data engineering, Azure FinOps and cost optimization, data analysis, and visualization experience. You will work with large and complex datasets, develop scalable data pipelines, provide actionable insights, and collaborate closely with technical and business stakeholders to ensure data is accessible, reliable, and cost-efficient. This is an opportunity for someone who can bridge data engineering and analytics, translating complex data into meaningful insights while helping optimize the performance and cost of our Azure and Databricks environment.
Accountabilities
- Evaluate business needs to determine data and infrastructure requirements.
- Design and maintain scalable, high-performance data pipelines and architectures.
- Ingest and process raw data from a variety of sources, both batch and streaming.
- Assemble large, complex datasets that support business intelligence, analytics, and machine learning use cases.
- Collaborate with cross-functional teams to understand data requirements, business operations, and deliver effective data solutions.
- Identify, design, and implement internal process improvements (e.g., automating manual processes, optimizing data delivery, re-architecting infrastructure).
- Conduct data profiling and performance analysis. Collate and publish statistics, metadata, and summaries, and analyze and optimize the performance of data pipelines.
- Build tools and systems that support data transformation, data quality, and governance.
- Monitor, report, and optimize cloud cost consumption. Develop and implement techniques to optimize cost and performance.
- Support analytics and data science teams with tooling and data accessibility.
Qualifications
Education & Experience
- 3+ years of experience as a Data Engineer or Data Analyst role.
- Bachelor’s degree in computer science or a related field.
- Strong communication and stakeholder management skills.
- Strong proficiency in Python for data engineering tasks.
- Advanced SQL skills and experience with relational databases (e.g., PostgreSQL).
- Experience building and maintaining ETL/ELT pipelines.
- Strong experience in Databricks AI/BI.
- Experience in Azure cloud data platform.
- Experience with data warehouse design, data modeling, and partitioning strategies.
- Comfortable working with structured and unstructured data.
- Knowledge of data governance practices, including cataloging, lineage, and compliance.
- Familiarity with version control (e.g., Git).
- Exposure to CI/CD for data workflows.
