Description

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Spark (Scala/Python), AWS Glue, AWS Lambda, and Shell scripting.

• Build, optimize, and support ETL/ELT workflows across AWS data platforms, including Amazon S3, Hive, Apache Iceberg, and Amazon Redshift.

• Develop and maintain Redshift SQL/PLSQL code, stored procedures, and enterprise data processing frameworks.

• Optimize database performance through query tuning, workload optimization, and efficient data-sharing implementations.

• Design and support ingestion frameworks for structured and semi-structured data formats, including JSON, CSV, XML, ORC, Parquet, and Avro.

• Design, implement, and support enterprise Customer 360 solutions that provide a unified view of customer data across multiple systems.

• Integrate data from multiple enterprise applications and business systems to support reporting, analytics, and customer engagement initiatives.

• Collaborate with business stakeholders and technical teams to define scalable data architecture and engineering solutions.

• Support Data Subject Requests (DSRs), including customer data deletion and privacy compliance processes.

• Partner with Data Protection Office (DPO) teams to ensure compliance with privacy regulations, governance policies, and enterprise data standards.

• Maintain and support enterprise privacy compliance solutions, including the MicroStrategy Privacy Compliance module.

• Contribute to enterprise data governance initiatives that improve data quality, consistency, metadata management, and compliance.

• Analyze and troubleshoot complex data quality, reporting, and platform issues using Redshift SQL, MySQL, Python/PySpark, Shell scripting, and Excel.

• Investigate data discrepancies, reporting anomalies, and customer data issues while performing root cause analysis and implementing corrective actions.

• Support analytics related to customer segmentation, loyalty programs, and customer engagement initiatives.

• Provide production support for enterprise data platforms and resolve critical production issues.

• Participate in enterprise initiatives related to Customer 360, Privacy, Data Governance, and data modernization programs.

• Conduct code reviews, design reviews, and provide technical guidance to engineering teams.

• Research, design, and implement next-generation data engineering capabilities and cloud-native data solutions.

• Serve as a subject matter expert for enterprise customer data platforms and cloud data engineering technologies.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related field, or equivalent professional experience.

• 12+ years of experience in Data Warehouse, Big Data, or Enterprise Data Engineering environments.

• 5+ years of experience in a Lead Data Engineer, Technical Lead, or Subject Matter Expert (SME) role.

• Strong experience designing and developing enterprise data pipelines using Spark (Scala/Python).

• Extensive experience with AWS services, including Amazon S3, EC2, Redshift, AWS Glue, Lambda, Kafka, Airflow, Hive, and Apache Iceberg.

• Strong experience developing ETL/ELT frameworks and enterprise data integration solutions.

• Experience developing and optimizing Redshift SQL/PLSQL, MySQL, stored procedures, and database performance.

• Strong understanding of data architecture, dimensional modeling, distributed data processing, and cloud-native data platforms.

• Experience designing and supporting enterprise Customer 360 or customer data platforms.

• Knowledge of data governance, privacy compliance, and enterprise data security principles.

• Experience working with structured and semi-structured data formats, including JSON, CSV, XML, ORC, Parquet, and Avro.

• Strong analytical, troubleshooting, and root cause analysis skills.

• Excellent verbal and written communication skills with the ability to collaborate across technical and business teams.

• Experience managing enterprise-scale data platforms and delivering complex data engineering initiatives.

Preferred Qualifications

• Experience in large enterprise or global delivery environments.

• Experience supporting cloud modernization and enterprise data transformation initiatives.

• AWS, Azure, GCP, or Data Engineering certifications.

• Experience working in regulated industries such as Hospitality, Finance, Healthcare, Telecommunications, or similar sectors.

• Experience leading enterprise data governance and customer data management initiatives.

• Strong leadership, stakeholder management, and mentoring experience.

• Experience working in Agile software development and data engineering environments

Key Skills

Education

Bachelor's degree