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Job Location: Chennai
- Works with business units and Product Dev teams to design, develop and deliver data solutions on one of the largest data platforms in the world.
- Supports business units by providing data in a ready-to-use form to data analysts and data scientists for Business insights, predictive analytics, machine learning, etc.
- Owns and accountable for the design and development of a Data solution feature or a Data Pipeline
- Spends most of the time developing data pipelines/ETL code for solving various data requirements using traditional ETL tools but also has experience skills for building custom data pipelines.
- Code is well-commented, easy to maintain, and can be reused across a sub-system or feature. Code may persist for the lifetime of a software version
- Code is thoroughly tested with very few bugs, and is supported by unit tests. Able to lead feature or sub-system design reviews and code reviews and be recognized as the go-to developer for that component.
- Leads in architecture discussions, proposes and discusses solutions to system and product changes.
- Should be comfortable working in an agile environment and with cross-functional teams, should have appetite to learn and be flexible to pick up new technology.
Skills and Experience
- A Master or Bachelor degree in computer science or equivalent with 10+ years of data engineering experience
- Good understanding of Data Warehousing and Business Intelligence Application Design Development.
- Good understanding of Data Modelling Concepts.
- Deals with both structured and unstructured data sets hence uses different methods to data architecture and applications in building data pipeline.
- ETL Development including various big data technologies, open source data ingestion and processing frameworks
- Gains experience with various big-data technologies and solutions (Hive, Pig, Spark) to optimize processing of extremely large datasets.
- Excellent debugging skills with a solid understanding of data and testing to capture data quality gaps/issues.
- Good understanding of data processing, data structure optimization and design for scalability.
- Can be relied on to deliver a data pipeline feature/component on time and to requirements, without data quality issues.
- Understands and is able to reason about the business requirements, as it relates to their area of expertise/SME.
- Develops the ability to help in resolving data issues.
- Understanding of with version control systems, particularly GIT.
- Strong analytical and problem solving skills.
- Good understanding of database principles and SQL beyond just data access.
- Proficient in scripting languages, i.e. Unix/Linux Shell Scripting
Intermediate level knowledge on following technologies, with expertise on few of them:
- Data Transformation tools like informatica
- Strong Database fundamentals (Oracle)
- HBase
- Hive/Pig
- Scripting (Shell, Python, Java, Scala)
- Hadoop eco system
- Elastic search
- Stream processing (Kafka)
Intermediate level knowledge on following business domains is a plus:
- Payments and banking
- Merchant servicing
- E-commerce
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