Senior Manager Software Engineering

Publicis Groupe ANZ; Bengaluru; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

Publicis Groupe ANZ seeks a Senior Manager of Software Engineering in Bengaluru, India. This role focuses on leading a high-performing engineering team to deliver scalable data platforms and set architectural standards in digital marketing.

The ideal candidate has over 10 years of engineering experience, with proven leadership in big data technologies such as Scala and AWS. Responsibilities include mentoring engineers, driving project execution, and ensuring system reliability.

Qualifications

• 10+ years of software engineering experience.
• 3–4+ years managing and leading engineering teams.
• Experience with big data and cloud-native systems.

Responsibilities

• Lead a team of engineers to deliver scalable data platforms.
• Drive architectural decisions for data processing systems.
• Ensure systems meet standards for scalability and reliability.

Skills

Software Engineering

Team Leadership

System Design

Stakeholder Management

Big Data Technologies

Tools

Scala

Apache Spark

AWS

Docker

Kubernetes

Job description

Overview

The Product team forms the crux of our powerful platforms and helps connect millions of customers worldwide with the brands that matter most to them. This team develops products that position us as a differentiator, encouraging an open and balanced marketplace built on respect for individuals, where every brand interaction holds value. Our full‑cycle product engineering and data teams use industry‑standard methodologies and sophisticated capabilities in data, machine learning, and artificial intelligence to chart the future and set new benchmarks for our products.

Senior Manager Software Engineering who leads a high‑performing engineering organization building scalable, data‑intensive platforms in the digital marketing and attribution space. The role combines people leadership, delivery ownership, and architectural influence with deep hands‑on credibility in big data, batch processing, and cloud‑native distributed systems.

Responsibilities

• Lead, mentor, and grow a team of data‑platform engineers delivering critical platform capabilities.
• Own execution, delivery predictability, and technical quality for the team.
• Drive architectural decisions and engineering best practices for the data‑processing systems.
• Partner with product managers to define roadmaps and translate business goals into technical plans.
• Foster a culture of ownership, accountability, and continuous improvement.
• Provide regular feedback, coaching, and career development guidance.
• Ensure systems meet standards for scalability, performance, security, and reliability.
• Improve engineering processes, CI/CD maturity, and operational excellence.

What You Will Achieve

• Build and sustain a high‑performing, engaged engineering team.
• Deliver scalable, reliable platforms that support growing data and traffic demands.
• Improve system observability, stability, and operational maturity.
• Set a higher standard on engineering quality and execution across teams.

Management Qualifications

• 10+ years of software engineering experience.
• 3–4+ years managing and leading engineering teams.
• Strong system design, communication, and stakeholder management skills.
• Experience defining and tracking engineering metrics (delivery, quality, reliability).
• Ability to mentor junior and mid‑level engineers and develop future technical leaders.

Technical Depth

• Domain & Product Focus:
  • Attribution product development.
  • Design, implement, and optimize data processing and batching solutions at scale.
  • Build, schedule, and maintain DAG workflows and attribution/forecasting engines.
  • End‑to‑end ownership: requirements definition, development, documentation, and stakeholder collaboration.

Core Technical Stack

• Big Data: Scala, Apache Spark, Hadoop (HDFS, YARN, MapReduce).
• Languages: Scala (primary), Python (infrastructure modules).
• Cloud: AWS (primary), GCP as needed; cloud‑native distributed systems.
• Data: SQL at terabyte scale, RDBMS/warehouse, performance optimization, operability.
• Workflows: DAG scheduling, batch pipeline orchestration.
• DevOps: Docker, Kubernetes, CI/CD pipelines, Git.
• Testing: Unit and integration test frameworks.

Nice to Have / Advantageous

• Databricks – Notebooks, Delta Lake, Catalogues.
• Observability & analytics – Tableau, Power BI, Grafana.
• Event‑driven / streaming architectures.
• Experience in ad‑tech / martech and large‑scale data platforms.

Epsilon is an Equal Opportunity Employer.

Epsilon is committed to promoting diversity, inclusion, and equal employment opportunities by using reasonable efforts to attract, recruit, engage and retain qualified individuals of all ethnicities and backgrounds, including, but not limited to, women, people of color, LGBTQ individuals, people with disabilities and any other underrepresented groups, traits or characteristics.