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Job Description & How to Apply Below
Job Summary
The data wranglers of the business world transform raw data into a usable format for analysis, building the infrastructure that empowers data scientists and analysts to unlock valuable insights. By identifying trends and developing strategies, they bridge the gap between data and actionable decisions, ultimately driving organizational efficiency and performance.
Job Qualifications- At least 5+ years’ experience with Spark
SQL, Python and PySpark for data engineering workflow - Strong proficiency in dimensional modeling and star schema design for analytical workloads
- Experience implementing automated testing and CI/CD pipelines for data workflows
- Familiarity with Git Hub operations and collaborative development practices
- Demonstrated ability to optimize engineering workflow jobs for performance and cost efficiency
- Experience with cloud data services and infrastructure (AWS, Azure, or GCP)
- Proficiency with IDE tools such as Visual Studio Code for efficient development
- Experience with Databricks platform will be a plus
- Design and implement ETL/ELT pipelines using Spark SQL and Python within Databricks Medallion architecture
- Develop dimensional data models following star schema methodology with proper fact and dimension table design, SCD implementation, and optimization for analytical workloads
- Optimize Spark SQL and Data Frame operations through appropriate partitioning strategies, clustering and join optimizations to maximize performance and minimize costs
- Build comprehensive data quality frameworks with automated validation checks, statistical profiling, exception handling, and data reconciliation processes
- Establish CI/CD pipelines incorporating version control, automated testing including but not limited to unit test, integration test, smoke test, etc.
- Implement data governance standards including row-level and column-level security policies for access controls and compliance requirements
- Create and maintain technical documentation including ERDs, schema specifications, data lineage diagrams, and metadata repositories
We are an equal opportunity employer who knows that each employee is unique - that’s what makes our team so great!
- Location(s): - Head Office - MT Haryono
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