Python
Java
Amazon Web Services (AWS)
Machine Learning (ML)Job Title: Engineering Manager
Job Location: Chennai, Bangalore
Job Summary
The Engineering Org is looking for a proficient Engineering Manager to join a team that is building exciting
and futuristic Data Products at Condé Nast to enable both internal and external marketers to target
audiences in real time. As an Engineering Manager, you will drive the day-to-day execution of technical
and architectural decisions. EM will own engineering deliverables inclusive of solving dependencies
such as architecture, solutions, sequencing, and working with other engineering delivery teams.This role
is also responsible for driving innovation, prototyping, and recommending solutions. Above all, you will
influence how users interact with Conde Nast’s industry-leading journalism.
● Primary Responsibilities
● Manage a high performing team of Software and Data Engineers within the Data & ML
Engineering team part of Engineering Data Organization.
● Provide leadership and guidance to the team in Data Discovery, Data Ingestion, Transformation
and Storage
● Utilizing product mindset to build, scale and deploy holistic data products after successful
prototyping and drive their engineering implementation
● Provide technical coaching and lead direct reports and other members of adjacent support teams
to the highest level of performance..
● Evaluate performance of direct reports and offer career development guidance.
● Meeting hiring and retention targets of the team & building a high-performance culture
● Handle escalations from internal stakeholders and manage critical issues to resolution.
● Collaborate with Architects, Product Manager, Project Manager and other teams to deliver high
quality products.
● Identify recurring system and application issues and enable engineers to work with release teams,
infra teams, product development, vendors and other stakeholders in investigating and resolving
the cause.
● Required Skills
● 4+ years of managing Software Development teams, preferably in ML and Data
Engineering teams.
● 4+ years of Agile Software development practices
● 12+ years of Software Development experience.
● Excellent Problem Solving and System Design skill
● Hands on: Writing and Reviewing code primarily in Spark, Python and/or Java
● Hand on: Architect & Design end to end Data Pipeline (noSQL databases, Job Schedulers, Big
Data Development preferably on Databricks / Cloud)
● Experience with SOA & Microservice architecture
● Knowledge of Software Engineering best practices with experience on implementing CI/CD,
Log aggregation/Monitoring/alerting for production system
● Working Knowledge of cloud and devops skills (AWS will be preferred)
● Strong verbal and written communication skills.
● Experience in evaluating team member performance and offering career development
guidance.
● Experience in providing technical coaching to direct reports.
● Experience in architecting highly scalable products.
● Experience in collaborating with global stakeholder teams.
● Experience in working on highly available production systems.
● Strong knowledge of software release process and release pipeline.
About Condé Nast
CONDÉ NAST INDIA (DATA)
Over the years, Condé Nast successfully expanded and diversified into digital, TV, and social
platforms - in other words, a staggering amount of user data. Condé Nast made the right move to
invest heavily in understanding this data and formed a whole new Data team entirely dedicated to
data processing, engineering, analytics, and visualization. This team helps drive engagement, fuel
process innovation, further content enrichment, and increase market revenue. The Data team
aimed to create a company culture where data was the common language and facilitate an
environment where insights shared in real-time could improve performance.
The Global Data team operates out of Los Angeles, New York, Chennai, and London. The team at
Condé Nast Chennai works extensively with data to amplify its brands' digital capabilities and boost
online revenue. We are broadly divided into four groups, Data Intelligence, Data Engineering, Data
Science, and Operations (including Product and Marketing Ops, Client Services) along with Data
Strategy and monetization. The teams built capabilities and products to create data-driven solutions
for better audience engagement.
What we look forward to:
We want to welcome bright, new minds into our midst and work together to create diverse forms of
self-expression. At Condé Nast, we encourage the imaginative and celebrate the extraordinary. We
are a media company for the future, with a remarkable past. We are Condé Nast, and It Starts Here.
Shubham Vishwakarma
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