Client Manager at ABC Consultants
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Lead - Data Analytics & Intelligence - BFSI (9-10 yrs)
Education - Tier1/2 Institutes
Roles & Responsibilities :
- Minimum 9 years of Data experience and 5 years in large scale Data Lake ecosystem
- Clean, prepare and optimise data at scale for ingestion and consumption
- Drive the implementation of new data management projects and re-structure of the current data architecture.
- Work with business stakeholders to identify and document high impact business problems and potential solutions
- First-hand experience with the complete software development life cycle including requirement analysis, design, development, deployment, and support
- Advanced understanding of Data Lake/Lake house architecture and experience/exposure to Data bricks techniques
- Work on end-to-end data lifecycle from Data Ingestion, Data Transformation and Data Consumption layer. Versed with API and its usability
- A suitable candidate will also be proficient Scala, Spark, Spark Streaming, AWS, and EMR
- A suitable candidate will also demonstrate machine learning experience and experience with big data infrastructure inclusive of Map Reduce, Hive, HDFS, YARN, HBase, Oozie, etc.
- The candidate will additionally demonstrate substantial experience and a deep knowledge of data mining techniques, relational, and non-relational databases.
Secondary Responsibilities :
- Implement complex automated workflows and routines using workflow scheduling tools
- Build continuous integration, test-driven development and production deployment frameworks
- Excellent oral and written communication skills Learn and use internally available analytic technologies
- Build models at scale using vast amounts of structured and unstructured heterogeneous types of data
- Identify key performance indicators and establish strategies on how to deliver on these key points for analysis solutions Use educational background in data engineering and perform data mining analysis
- Work with BI analysts/engineers to create prototypes, implementing traditional classifiers and determiners, predictive and regressive analysis points
- Engage in the delivery and presentation of solutions Participate in data storage architecture design discussions
- Apply machine learning and/or statistical techniques to time series classification and telemetry anomaly detection problems
Key Success Metrics :
- Ensure timely deliverables.
- Spot Data fixes.
- Lead technical aspects of the projects.
- Error free deliverables.
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