Job Description

In your work, you will advise clients on their data strategy, design solution architectures and lead teams in their journey to continuously develop and deploy these platforms.


1. Building, leading and growing a world-class Big Data and Machine Learning Team.
2. Provide cloud practice adoption, technology expertise, and process optimization blueprints for enterprise initiatives.
3. Aligning the Big Data and Machine Learning product and service roadmap with the overall company strategic goals and technical vision.
4. Acting as a strategic technology partner and service provider for our Big Data and Machine Learning business segments and related technology by developing and delivering on Big Data and Machine Learning technology roadmap.
5. Partnering with business segment and technology platform product management to ensure the proper positioning and adoption of cloud infrastructure technology products and services.
6. Lead a team of data engineers and guide them with the best data strategies in line with data needs.
7. Identifying, designing, and implementing process improvements that include building/re-engineering data models, data architectures, pipelines, and data applications.
8. Continuously look for data optimization processes and oversee data management, governance, security, and analysis for each project.
9. Build team, identify the potential of each team member and offer technical guidance, leadership, and advice on planning, designing, and implementing data solutions.
10. Manage data delivery through high-performing dashboards, visualizations, and reports for our clients.
11. Ensure data quality and security across every product vertical and related areas.
12. Design, create and launch new data models and pipelines as per needs.
13. Act as a mentor and grow the team by hiring skilled data engineers.
14. Work towards achieving high performance, operational excellence, accuracy, and reliability of the overall system.
15. Mentor and grow data warehouse, data modeling, and data visualization team to correctly establish a data-driven culture.
16. Utilize tools and technologies to create data architecture that supports new data initiatives and is useful in next-gen products.
17. Ensure test-driven products/pipelines that are easily maintainable and reusable.
18. Design and build an infrastructure for extraction, transformation, and loading of data from a wide range of data sources.
    

Requirements:

1. Minimum 5 years of experience related to Big Data or Machine Learning.
2. Have a good understanding of Databases (RDBMS, NON-RDBMS).
3. Have a good understanding of ETL/ELT.
4. Have a good understanding of Data and Business Analytics.
5. Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming.
6. Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
7. Experience with Spark.
8. Experience with integration of data from multiple data sources.
9. Experience with NoSQL databases, such as HBase, Cassandra, MongoDB.
10. Knowledge of various ETL techniques and frameworks, such as Flum