Data Operations Engineer

Overview

Apply best practices for data quality & triaging - (with goal to reduce data downtimes) on existing and new pipelines for our business, customer and Data Science team.

Responsibilities

• Own data quality from existing data pipelines, development end-to-end quality framework spanning outages, freshness, accuracy.
• Work with teams like product catalog on product classification, Supply Chain & MKT on data validations.
• Work with the product team leveraging our core technology platforms, which include Direct Commerce, Supply Chain, Marketing Automation, Mobile, and Data. Collaborate to triage continuously improving data quality, matching data across various downstream and upstream systems.
• Enable framework development for data quality in collaboration with other engineers validate requirements / stories, assess current capabilities.
• Partner with software engineering teams that build frameworks on MonteCarlo / Great Expectations / Sentry in short iterations to quickly add business value.
• Help Implement new tools / practices to improve data and code quality this includes researching / sourcing 3rd party tools and libraries, as well as developing tools in-house to improve workflow and quality for all data engineers and operations team's members.

Qualifications

• Master's or bachelor's degree in computer engineering or related analytics field from a premier/Tier1 institute of India.
• Total Experience - 7-9 Years
• 4+ years of experience in designing and building systems for collecting, storing, and analyzing data at scale.
• Required skills: Python, SQL, AWS, Azure, familiarity with BI tools (PBI/Tableau).
• Strong interpersonal skills to effectively interact with client/onshore personnel to understand specific Enterprise Information Management requirement and develop solutions based on that requirement.
• Experience in Retail, E-commerce or Financial Services domain is preferred.
• Very strong analytical skills with the demonstrated ability to research and make decisions based on the day-to-day and complex customer problems required.
• Hands on experience of handling large data sets and use of python /SQL for data analysis.
• Strong record of achievement, solid analytical ability, and an entrepreneurial hands-on approach to work.
• Outstanding written and verbal communication skills.