Senior Data Engineer

Roles & Responsibilities:

1. Passionate about building next generation data platforms and data pipeline solution across the bank.
2. Enthusiastic, be able to contribute and learn from wider engineering talent in the team.
3. Ready to execute state-of-the-art coding practices, driving high quality outcomes to solve core business objectives and minimise risks.
4. Capable to create both technology blueprints and engineering roadmaps, for a multi- year data transformational journey.
5. Can lead and drive a culture where quality, excellence and openness are championed.
6. Constantly thinking outside the box and breaking boundaries to solve complex data problems.
7. Have experience in providing data driven solutions that source data from various enterprise data platform into Cloudera Hadoop Big Data environment, using technologies like Spark, MapReduce, Hive, Sqoop, Kafka; transform and process the source data to produce data assets; and transform and egression to other data platforms like Teradata or RDBMS system.
8. Are experienced in building effective and efficient Big Data and Data Warehouse frameworks, capabilities, and features, using common programming language (Scala, Java, or Python), with proper data quality assurance and security controls.
9. Are experienced in providing data driven solutions in the Cloud to build various enterprise data platform into AWS platform using technologies like S3, EMR, Glue, Iceberg, Kinesis or MSK/Kafka; transform and process the data to produce data assets for Redshift and DocumentDB.
10. Are confident in building group data products or data assets from scratch, by integrating large sets of data derived from hundreds of internal and external sources.
11. Can collaborate, co-create and contribute to existing Data Engineering practices in the team.
12. Have experience and responsible for data security and data management.
13. Have a natural drive to educate, communicate and coordinate with different internal stakeholders.

Essential Skills:

1. Preferably with at least 8+ years of hands-on experience in a Data Engineering role.
2. Experience in designing, building, and delivering enterprise-wide data ingestion, data integration and data pipeline solutions using common programming language (Scala, Java, or Python) in a Big Data and Data Warehouse platform.
3. Experience in building data solution in Hadoop platform, using Spark, Hive,MapReduce, Sqoop, Kafka and various ETL frameworks for distributed data storage and processing. Preferably with at least 8+ years of hands-on experience.
4. Experience in building data solution using AWS Cloud technology (EMR, Glue, Iceberg, Kinesis, MSK/Kafka, Redshift, DocumentDB, S3, etc.). Preferably with 2+ years of hands-on experience and certified AWS Data Engineer.
5. Strong Unix/Linux Shell scripting and programming skills in Scala, Java, or Python.
6. Proficient in SQL scripting, writing complex SQLs for building data pipelines.
7. Experience in working in Agile teams, including working closely with internal business stakeholders.
8. Familiarity with data warehousing and/or data mart build experience in Teradata, Oracle or RDBMS system is a plus.
9. Certification on Cloudera CDP, Hadoop, Spark, Teradata, AWS, Ab Initio is a plus.
10. Experience in Ab Initio software products (GDE, Co>Operating System, Express>It, etc.) is a plus.

Educational Qualifications: B.Tech and above