Data Engineer – Master Data Management

Summary of Position:

• This role is responsible for the Data Engineering of Master Data Management (MDM) data within Alcons AWS data lake environment. Working closely with business and data governance stakeholders the Data Engineer will design build and optimize scalable data pipelines that ingest cleanse transform and provision trusted master data with a primary focus on Customer Master data and Product Information Management (PIM) data domains in alignment with Alcons Data and Analytics strategy standards and governance practices.
• Knowledge of Customer Master data and Product Information Management (PIM) data domains is highly preferred.

Key Responsibilities:

• Design build and maintain scalable data pipelines to ingest cleanse transform and curate Master Data Management (MDM) data especially Customer Master and Product Information Management (PIM) data within the AWS data lake.
• Adopt AWS data lake and related data services to implement end-to-end MDM data solutions across ingestion integration curation and consumption.
• Deliver business solutions on Alcons analytics platform through end-to-end implementation that includes data security governance cataloging preparation automated testing and data quality metrics.
• Build data pipelines using Python PySpark and Spark SQL integrating master data from a variety of heterogeneous source systems.
• Collaborate with data governance teams and information stewards to support data quality stewardship matching/survivorship and lifecycle management for Customer Master and PIM data.
• Automate optimize migrate and enhance existing MDM data solutions and pipelines.
• Perform data modeling data analysis and provide insights that support trusted customer and product master data for downstream analytics use cases.
• Participate in backlog grooming sprint planning and effort estimation as part of an agile DevOps team.
• Analyze and manage master data within Master Data Management (MDM) platforms such as Reltio including customer product supplier and reference data domains.
• Configure maintain and analyze Product Information Management (PIM) solutions such as Stibo to ensure high-quality product content digital assets classifications attributes and product lifecycle data.
• Utilize data cataloging and metadata management tools to document classify govern and improve discoverability of enterprise data assets business glossaries lineage and data quality metrics.

Key Requirements/Minimum Qualifications:

• Education: / B.E / / MCA or bachelors/masters degree in Computer Science Data Science or a related quantitative field (or equivalent applicable experience).
• 6 to 10 years of experience in Big Data / data lake solutions in an AWS cloud environment.
• 3 years of experience writing code in the Spark engine using Python Scala or Java.
• Hands-on experience building and optimizing data pipelines for data ingestion preparation curation provisioning automated testing and quality checks.
• Good working knowledge of AWS services such as Glue EMR S3 SNS SQS Athena Redshift Lambda and Step Functions.
• Good experience in RDBMS MS SQL Oracle Postgres etc.; strong working knowledge of SQL is a must.
• Experience performing data modeling data analysis and deriving insights using various tools.
• Experience working as part of agile teams using collaboration tools such as Jira and Confluence.
• Ability to work with the business to capture groom prioritize plan and demo User Stories.
• Familiarity with visualization and reporting tools such as Tableau or AWS Quick.

Highly Preferred

• Knowledge of and hands-on experience with Master Data Management (MDM) concepts tooling and processes.
• Working knowledge of Customer Master data domains (customer records hierarchies matching de-duplication and survivorship).
• Working knowledge of Product Information Management (PIM) data domains (product attributes catalogs taxonomies and enrichment).
• Understanding of data governance data quality and stewardship practices as applied to master data.

Interpersonal Skills & Characteristics

• Strong collaboration skills for effective communication across multiple teams and stakeholders both internal and external.
• Data-savvy individual with hands-on experience preparing analyzing and deriving insights from data.
• Confident energetic self-starter with strong problem-solving ability and high learning agility.
• Demonstrated commitment to high standards of ethics regulatory compliance customer service and business integrity.

Work hours: 1 PM to 10 PM IST

Relocation assistance: Yes

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