Manager Data Engineering

Manager – Data Engineering Publicis Sapient is seeking a Manager – Data Engineering to join our high-performing engineering team.

In this role, you will lead the design and delivery of scalable, cloud native data engineering solutions, partnering with clients and cross-functional teams to solve complex business challenges.

You will provide technical leadership, drive architecture decisions, mentor engineering teams, and ensure the successful implementation of modern data platforms that power analytics, AI, and digital transformation initiatives.

As a Manager, you will combine deep technical expertise in big data and cloud technologies with strong consulting, stakeholder management, and people leadership capabilities to enable clients to unlock value from enterprise-scale data ecosystems.

Your Impact:

• Lead the design, architecture, and delivery of large-scale data engineering solutions across cloud and hybrid environments.
• Drive end-to-end data platform implementations encompassing data ingestion, transformation, storage, processing, governance, and consumption.
• Architect batch and real-time data pipelines leveraging modern big data frameworks and cloud-native services.
• Provide technical leadership and hands-on guidance to engineering teams, ensuring solution quality, scalability, security, and operational excellence.
• Lead architecture reviews, technical design discussions, and solution governance activities.
• Establish best practices in data engineering, including coding standards, performance optimization, security, and reliability.
• Collaborate with business stakeholders, architects, product teams, and clients to translate business requirements into scalable technical solutions.
• Mentor and develop engineering talent, contributing to hiring, capability building, and technical community initiatives.
• Drive cloud transformation programs utilizing AWS, Azure, or GCP data platforms.
• Promote innovation, thought leadership, and adoption of emerging technologies including GenAI-enabled data engineering solutions.

• 8+ years of IT experience, with 5+ years in data engineering, big data, or related technologies.
• Proven experience leading the design and delivery of enterprise-scale data engineering solutions.
• Strong hands-on expertise in at least one cloud platform (Azure as Primary; along with AWS/GCP experience).
• Advanced programming expertise in Python (Scala as secondary).
• Deep experience with distributed data processing frameworks such as Spark, Flink, Storm, or Hadoop ecosystem technologies.
• Expertise in data ingestion and streaming frameworks including Kafka, NiFi, Pulsar, Pub/Sub, or similar platforms.
• Experience building batch and real-time ETL/ELT pipelines at enterprise scale.
• Strong understanding of cloud-based data architecture patterns and modern data platform design.
• Experience with orchestration tools such as Airflow, Oozie, Control-M, or equivalent scheduling frameworks.
• Working knowledge of NoSQL and MPP platforms including MongoDB, Cassandra, HBase, BigQuery, Redshift, Athena, Presto, or Impala.
• Strong understanding of data security, IAM, encryption, privacy, governance, and compliance requirements.
• Experience with monitoring, observability, and operational management of large scale data platforms.
• Hands-on experience with performance tuning and optimization of data pipelines and distributed computing workloads. Leadership & Consulting Responsibilities
• Lead engineering teams in delivering high-quality, scalable solutions across multiple engagements.
• Partner with clients to define technology strategies and recommend optimal data platform solutions.
• Facilitate technical workshops, architecture reviews, and stakeholder alignment sessions.
• Drive agile delivery practices and ensure successful program execution.
• Provide mentorship and career development support for engineers and technical leads.
• Contribute to organizational capability-building initiatives and recruitment efforts.
• Champion innovation, reusable frameworks, and engineering best practices across programs.

Bachelor’s or Master’s Degree in Computer Science, Computer Engineering, Information Technology, or a related technical field.

Additional information Set Yourself Apart With:

• Experience with data governance platforms such as Collibra, Alation, Data Catalog, Lineage, and Metadata Management solutions.
• Knowledge of relational, NoSQL, columnar, and MPP database technologies.
• Experience with CI/CD pipelines, Infrastructure as Code, and automated cloud deployment practices.
• Exposure to containerization and orchestration technologies including Docker and Kubernetes.
• Strong understanding of dimensional modeling, star schema, snowflake schema, and modern data warehouse architectures.
• Experience implementing cloud-native lakehouse architectures and modern data mesh concepts.
• Thought leadership contributions including blogs, whitepapers, technical talks, hackathons, or conference presentations.
• Relevant cloud, data engineering, or big data certifications.
• Exposure to Generative AI, AI/ML data platforms, and modern analytics ecosystems. Personal Attributes
• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management capabilities.
• Strong leadership, mentoring, and collaboration skills.
• Ability to influence technical and business decision-making.
• Self-driven with strong ownership and accountability.
• Comfortable working in global, distributed, and cross-functional teams.
• Proven ability to manage multiple priorities in fast-paced environments.

of Working Here: Gender-Neutral Policy 18 paid holidays throughout the year.

Generous parental leave and new parent transition program Flexible work arrangements Employee Assistance Programs to help you in wellness and well-being.