Senior Data Analytics Developer

We are seeking a talented and experienced Data Analytics Developer to join our team. You will play a key role in designing, developing, and maintaining our next-generation data analytics platform.

• Design, develop, and maintain data ingestion and processing pipelines to move large volumes of data from various sources into the data platform.
• Utilize Apache Druid to build high-performance, real-time analytics solutions, focusing on data ingestion, indexing, and query optimization.
• Leverage Starburst (Trino) to implement a data mesh architecture and enable query federation across different data sources, including data warehouses, data lakes, and other systems.
• Develop and optimize analytical queries and reporting views using SQL within Impala for high-performance interactive and batch queries on large datasets.
• Implement and manage datasets using Apache Iceberg, ensuring features like schema evolution, partitioning, and time-travel are leveraged for robust and reliable data lake operations.
• Apply OLAP (Online Analytical Processing) techniques and tooling to design and develop multidimensional data models (cubes) for fast and efficient analysis.
• Collaborate with data architects and business intelligence teams to create and maintain optimal data models and data warehouse structures.
• Troubleshoot and resolve performance issues, data processing bottlenecks, and data quality problems within the data analytics ecosystem.
• Maintain comprehensive documentation for all data processes, architectures, and data flows.

• 5-8 years of relevant experience
• Proven hands-on experience in a data engineering or analytics developer role.
• Strong expertise with SQL and experience with various data analytical tools.
• Deep experience with Apache Druid, including cluster management, data ingestion, and query optimization.
• Hands-on experience with Starburst (Trino), including query federation and performance tuning across data sources.
• Solid understanding and experience with Apache Impala for fast, interactive SQL queries on Hadoop or cloud data storage.
• Strong expertise with Apache Iceberg, including implementation for data lake architectures, schema evolution, and partitioning.
• Experience with OLAP cube development, including knowledge of multidimensional expressions (MDX) and best practices.
• Proficiency in one or more of Java, Python or PySpark for data processing and pipeline development is desirable.
• Experience with cloud platforms such as AWS, GCP, or Azure is a plus.

• 401k matching
• Health insurance
• Flight privileges

Discover your future at Citi