Job Description
Role: Data Engineering Manager
Location: Hyderabad
Experince: 12+ Yrs
Overview
Acxiom is seeking a Data Engineering Manager to lead the development and evolution of scalable, privacy-first data platforms that power identity resolution, data enrichment, and enterprise marketing solutions. This leader will oversee a team responsible for building high-volume, secure, and reliable data pipelines within Acxiom's cloud based Snowflake and Databricks ecosystem. The ideal candidate combines deep technical expertise in modern data engineering with strong leadership and delivery ownership. This role requires a strong understanding of PII data, data governance, and compliance in highly regulated environments, along with the ability to drive execution across multiple product and platform initiatives.
Key Responsibilities
Lead and develop a team of data engineers supporting Acxiom's identity and data product platforms
Coach & mentor team members, assisting them in overcoming obstacles to implementation and skills development
Architect and support scalable batch and near real-time data pipelines that process high-volume consumer and enterprise datasets
Participate in driving Snowflake platform strategy, including data modeling, performance tuning, workload optimization, and cost management
Collaborate with Architecture, Cloud Engineering and business process owners to design secure, resilient AWS-based solutions aligned with enterprise standards
Ensure compliance with data privacy regulations (CCPA, GDPR, and industry-specific standards) and enforce strong data governance controls
Collaborate with business process owners to Implement and maintain robust data quality frameworks, monitoring, lineage, and observability practices
Collaborate with Product, Identity Solutions, Analytics, and Security teams to translate business requirements into scalable data solutions
Lead design reviews and architectural discussions to maintain high engineering standards
Collaborate with DevOps to drive CI/CD, automation, and best practices within the data engineering lifecycle
Required Qualifications
Bachelor's degree in computer science, Engineering, or a related field
810 years of experience in data engineering, data platform development, or software engineering in large-scale data environments
3+ years of experience leading and developing engineering teams
Expert-level PySpark and SQL and strong experience designing scalable data models in Snowflake and Databricks
Proven experience building and optimizing data pipelines in AWS environments (S3, Lambda, Glue, IAM, etc.)
Experience working with large, complex datasets
Deep understanding of data governance, privacy, access controls, and secure data handling
Strong knowledge of CI/CD practices, automated testing, and DevOps principles
Ability to balance multiple high-priority initiatives in a fast-paced enterprise environment
Excellent communication and stakeholder partnership skills
