Manager / Senior Manager - Data Engineering - DF

About Us

Website : https : / / www.cognitioanalytics.com /

Cognitio Analytics, founded in 2013, aims to be the preferred provider of AI / ML driven productivity solutions for large enterprises. The company has received awards for its Smart Operations and Total Rewards Analytics Solutions and is dedicated to innovation, R&D, and creating sustained value for clients. Cognitio Analytics has been recognized as a 'Great Place to Work' for its commitment to fostering an innovative work environment and employee satisfaction.

Our solutions include Total Rewards Analytics powered by Cognitio's Total Rewards Data Factory, The Total Rewards Analytics solutions helps our clients achieve better outcomes and higher ROI on investments in all kinds of Total Rewards programs.

Our smart operations solutions drive productivity in complex operations, such as claims processing, commercial underwriting etc. These solutions, based on proprietary capabilities based on AI, advanced process and task mining, and deep understanding of operations drive effective digital transformation for our clients.

Relevant Experience : 8-12 years

Location : Gurgaon

Job Description

• Lead the data engineering team by driving the design, build, test, and launch of new data pipelines and models on the production data platform
• Define and implement the processes needed to achieve operational excellence in all areas, including agile development, and data solutions
• Oversee the design, development and maintenance of data infrastructure, including data warehouses, data lakes, data integration components supporting optimal extraction, transformation, and loading of data
• Leading the communication with vendors, clients, the leadership team, and other stakeholders to facilitate effective project management and provide ongoing support
• Collaborate with business owners for roadmap planning and prioritization, to deliver robust cloud-based data solutions for our customers
• Work closely with cross-functional teams to propel and execute necessary solution enhancements and provide support for existing solutions
• Define and enforce best practices for data engineering, data modeling, and data quality to ensure accuracy, reliability, reusability, security and consistency of data
• Evaluate and implement new technologies, tools, and frameworks to improve the performance and efficiency of the data engineering team
• Lead the planning, prioritization, and execution and tracking of data engineering projects, ensuring timely delivery and alignment with business objectives
• Establish and monitor key performance indicators (KPIs) to measure the performance and effectiveness of the data engineering team
• Stay current with industry trends and advancements in data engineering, Azure Cloud, and provide strategic guidance for adopting new technologies or methodologies

Qualifications

Skill Required

Must Haves :

Good To Have

Skills Required

Py Spark, Data Governance, Python, Azure Devops, Spark SQL, Data Modelling, Apache Spark, Datamart, Sql, Sdlc, Azure Data Factory, Databricks, Data Warehousing, Etl