We are looking for a Sr. Manager, Data Engineering to be part of our FP&A’s Digitization team in Noida, Uttar Pradesh, India. This role is expected to be 30% hands on execution building the solutions while the rest is overseeing the delivery and solutioning for the team.
In this role you can expect to drive the following-
Data Strategy and Alignment
- Work closely with Lead- business analysis and analytics to understand requirements and provide data ready for analysis and reporting.
- Apply, help define, and champion data governance : data quality, testing, documentation, coding best practices and peer reviews.
- Continuously discover, transform, test, deploy, and document data sources and data models.
- Develop and execute data roadmap (and sprints) - with a keen eye on industry trends and direction.
Data Stores and System Development
- Design and implement high-performance, reusable, and scalable data models for our data warehouse to ensure our end-users get consistent and reliable answers when running their own analyses.
- Focus on test driven design and results for repeatable and maintainable processes and tools.
- Create and maintain optimal data pipeline architecture - and data flow logging framework.
- Build the data schema, features, tools, and frameworks that enable and empower BI and Analytics teams across FP&A function.
Project Management
- Drive project execution using effective prioritization and resource allocation.
- Resolve blockers through technical expertise, negotiation, and delegation.
- Strive for on-time complete solutions through stand-ups and course-correction.
Team Management
- Manage and elevate team of 2 members.
- Do regular one-on-ones with teammates to ensure resource welfare.
- Periodic assessment and actionable feedback for progress.
- Recruit new members with a view to long-term resource planning through effective collaboration with the hiring team.
Process design
- Set the bar for the quality of technical and data-based solutions the team ships.
- Enforce code quality standards and establish good code review practices - using this as a nurturing tool.
- Set up communication channels and feedback loops for knowledge sharing and stakeholder management.
- Explore the latest best practices and tools for constant up-skilling.
Data Engineering Stack
- Programming : Python ( expert)level. Ability to create API’s on python.
- Database : PostgreSQL, Amazon Redshift
- Warehouse : Snowflake, S3
- ETL : DBT + Custom-made Python
- Business Intelligence / Visualization : M+ Google Data Studio
- Frameworks : Spark + Dash + Stream Lit
- Collaboration : Git, Notion
- Cloud Platform- AWS
Qualification Prerequisites
- Industry experience of minimum 12 years (2 years+ in snowflake)
- Experience managing a team of at least 4 developers end-to-end
- Strong hands-on data modelling and data warehousing skills
- Snowflake Certification is mandatory.
- Strong experience applying software engineering best practices to data and analytics scope (e.g. version control, testing, and CI/CD)
- Strong attention to detail to highlight and address data quality issues
- Excellent time management and proactive problem-solving skills to meet critical deadlines #LI-Onsite #LI-SG1
Canada, Colorado, California, Washington and New York Applicants: To view base salary ranges for this role in your location and to learn more about which roles are eligible for bonus pay or commissions, please visit our Pay Transparency Calculator below. Individual pay within the range will be determined based on job related-factors such as skills, experience, and education or training. Information on our benefits can be found via the link below. Intern ranges can be found below.
