- Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline
- 4+ years of industry experience in data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets
- Experience using big data technologies (Hadoop, Hive, HBase, Spark etc.)
- Demonstrated strength in data modeling, ETL development, and data warehousing
- Knowledge of data management fundamentals and data storage principles
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience with automation using either Shell scripting , Python or other similar languages
Finance Technology team is looking for a talented and passionate Senior Data Engineer with strong technical and business background. Our ideal candidate thrives in a fast-paced environment, relishes working with big data, enjoys the challenge of highly complex business contexts that are typically being defined in real-time. Our team operates platforms that are among the largest in the world by volume and complexity.
A successful candidate will have experience providing technical leadership and mentoring other engineers for best practices on data engineering. In this role, you will lead all aspects of the the design, creation, management, and business use of extremely large datasets. You will be responsible for owning the design of scalable processes to publish data and lead building of solutions to reconcile data for integrity and accuracy of financial data sets. You should have broad understanding of RDBMS, industry standard data replication solutions, NoSQL technologies , ETL , Big Data, Hadoop, Data Security, Data Integration, Data Warehousing, Data Governance and Data Lakes.
- Experience with AWS technologies including Redshift, RDS, S3, EMR, EML or similar solutions build around Hive/Spark etc.
- Experience with working data replication technologies
- Proficient in one of Programming languages (e.g., Python, Ruby, Shell Scripting, Java)
- Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
- Excellent knowledge of Advanced SQL working with large data sets.