Principal Data Engineer (I)

Job Summary

• The Principal Data Engineer is the leading technical voice in data engineering. This role champions strategic initiatives for advanced data platform solutions, acting as the primary technical liaison with leadership to ensure alignment on data strategies. Responsibilities include spearheading the design and implementation of innovative data platform technologies, offering strategic direction on industry-standard tools and architectures, and leading collaborations with enterprise partners. This position also oversees agile workflows, data product optimization, and comprehensive performance monitoring to support enterprise analytics and reporting.

Essential Job Functions

• Oversee and champion strategic initiatives for advanced data solutions. Act as the primary technical liaison with leadership, ensuring alignment on data strategies - (15%)
• Serve as the leading voice on cutting-edge data technologies. Spearhead the design and implementation of agile practices, fostering innovation and guiding the team on the latest industry trends and data platform solutions. - (15%)
• Possess deep expertise in industry leading Data Engineering tools. Provide oversight on adopting and leveraging tools ensuring alignment with enterprise cloud strategies. - (15%)
• Formulate and lead strategic collaborations with enterprise partners to enhance and expand data capabilities. Drive consensus and gain endorsement from governance teams, ensuring successful planning and execution of innovative data initiatives. - (15%)
• Define and advocate the strategic vision for data product/service, overseeing backlog management and market research to deliver pioneering solutions. Lead the architecture and optimization of advanced data solutions, focusing to drive efficiency. - (15%)
• Assume end to end responsibility for ensuring efficient workflows through the agile product management cycle. Prioritize technical design and delivery, while setting benchmarks for success criteria, testing, configuration, and coding standards. - (15%)
• Oversee comprehensive monitoring, reporting, and forecasting of data platform performance and costs. Continuously refine the business case to support strategic decision-making and resource allocation for assigned functions. - (10%)

Experience Range:-Minimum Qualifications

• Bachelors Degree r equivalent experience.
• 15+ years of work experience and knowledge of the major industry toolsets used in Data Engineering.
• Experience with relational (Microsoft SQL Server, Oracle), columnar (NoSQL), Hadoop Distributed File System/HDSF (Azure ADLS, AWS EMS, Databricks), and graph databases.
• Experience with ETL/ELT (Azure ADF, AWS Glue, Informatica) and on premise and cloud based data solutions.
• Experience developing systems intended for cloud deployments (AWS, EKS, lambdas, etc.). Exposure Azure data environment and familiarity with associated tools would be added advantage. Experience in modelling a third normal form, Star / Snowflake Data Warehouse system. Good experience in Data Profiling and Analysis

Preferred Qualifications

• Masters Degree in Computer Science or STEM field or equivalent experience.
• 17-19 years of work experience required in Data Engineering, DevOps, automated testing, statistical process controls, cloud engineering, data warehousing.
• Experience developing systems intended for cloud deployments (AWS, EKS, lambdas, etc.). Exposure Azure data environment and familiarity with associated tools would be added advantage.

Skills:-Skills

• Agile Methodology
• Apache Hadoop
• Cloudera Data Platform (CDP)
• Data Analysis
• Data Engineering
• Documentations
• Hadoop Distributed File System (HDFS)
• Platform Technologies
• Python (Programming Language)
• Solutions Design
• Structured Query Language (SQL)
• Commercial Acumen

Any Additional Preferences:-Travel

• Ability to travel up to 10% annually