Senior Analyst, Big Data Analytics & Engineering

- Partnering with data owners, engineering and platform teams to create robust data pipelines, create Data Products, implement data models.
- Ensure alignment between business goals and technical execution, making sure features and solutions meet business requirements and customer needs.
- Participate in sprint planning, retrospectives, and other agile ceremonies to ensure the team is aligned and delivering efficiently.
- Adoption of best practices in data engineering, automated code reviews, testing, and continuous integration/continuous delivery (CI/CD).
- Optimize the cost/benefit of implementing code a certain way, architecture alignment, ensuring scalability, performance, and operational efficiency.
- Ensuring solutions align with Mastercard’s engineering and data principles, and technical policies.
- Identify opportunities for process improvements, helping to streamline workflows and enhance team productivity.
- Stay abreast of Data Platform technology trends and industry best practices to hone and maintain your talent
- Participate in architectural discussions, iteration planning, and feature sizing meetings
- Adhere to Agile processes and participate actively in agile ceremonies

All About You
5+ years of hands-on experience building Data platforms (data lakehouses) developing solutions on on-prem / cloud.
- Proven experience as a hands-on data engineer, with a strong focus on delivering large-scale projects in an agile environment.
- Deep understanding and experience with Cloudera Data Platform (CDP)
- Strong hands-on experience with PySpark.
- Experience with Cloudera Data Platform (CDE, CDW, Ozone, Airflow, SDX), Apache Ranger
- Deep understanding of distributed data systems and Hive Metastore
- Experience and understanding of cataloging, lineage, and governance
- Experience / understanding Open Data Contract Standard (ODCS) and its implementation
- Experience working with SQL, file formats (Iceberg/Parquet), and partitioning/bucketing strategies.
- Prior experience with financial systems, such as Oracle Financials, Oracle Fusion Cloud, and Hyperion, with experience optimizing their integration into broader data ecosystems, is a plus.
- Experience with data lifecycle management, including ingestion, ETL, pruning, modeling, and governance, within highly regulated environment
-Experience and knowledge of Bit Bucket, Rally, and Jenkins a plus
-Understanding of SDLC and experience in establishing processes, standards and governance to bring efficiency within development team