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Hire(d) better.
Hire(d) better.
Data Engineering Manager
Riveron is seeking a hands-on Data Engineering Manager to be part of our data engineering team in India. This is not a pure people-management role — you will be writing code, building pipelines, and architecting data platforms daily alongside your team. We're looking for someone who leads from the codebase, not just from a conference room. If you bring deep implementation experience across Microsoft Fabric, Snowflake, and Databricks and can pair strong architectural thinking with real delivery output, we'd love to hear from you.
Who You Are:
A data engineering professional with 7-9 years of experience, including 1-3 years balancing technical leadership with active, hands-on implementation — you've managed teams without stepping away from the keyboard.
You write production-quality code daily. This role requires active coding and pipeline development — not just code reviews and architectural diagrams.
Hands-on, implementation-level expertise with Microsoft Fabric, Snowflake, and Databricks is non-negotiable. You've personally built, deployed, and tuned production workloads on these platforms.
Strong data architecture background spanning lakehouse design, medallion architecture, data vault, dimensional modeling, and enterprise data platform design — grounded in systems you've actually built, not just designed on paper.
Deep proficiency in SQL and Python — you can write complex transformations, optimize query performance, debug pipeline failures, and build automation frameworks yourself.
Proven experience building and shipping ETL/ELT frameworks using Azure Data Factory, dbt, Spark, and platform-native orchestration tools.
Solid working knowledge of Azure cloud data services (Synapse Analytics, Data Lake Storage, Azure SQL Database) and comfort operating in multi-cloud environments.
Well-versed in data governance, data quality frameworks, cataloging, lineage, and security best practices — with experience implementing these controls, not just defining policies.
Proficient with Git-based version control, CI/CD pipelines for data workloads, and Infrastructure as Code — you commit code, open pull requests, and maintain deployment pipelines alongside your team.
Comfortable working in Agile delivery environments and translating business requirements into scalable technical designs.
What You'll Do:
Spend a significant portion of your time writing code — building data pipelines, developing transformation logic, configuring platform services, and shipping production-ready solutions.
Lead, mentor, and grow a team of data engineers while remaining the team's strongest technical contributor and setting the standard through your own code and architectural decisions.
Design and personally implement scalable data platforms on Microsoft Fabric, Snowflake, and Databricks — selecting the right platform for each use case and building the solution end to end.
Architect and build lakehouse and data warehouse solutions, defining and coding ingestion patterns, transformation layers, storage strategies, and consumption models.
Own critical and complex implementation work — the toughest pipeline builds, the most challenging performance problems, and the architectural spikes that set direction for the team.
Write and maintain shared libraries, frameworks, and reusable components that accelerate the team's delivery and enforce engineering standards.
Conduct deep, line-level code reviews focused on correctness, performance, and maintainability — not just approval stamps.
Partner with analytics, data science, and business stakeholders to translate data requirements into engineered solutions, and personally prototype key components.
Establish and enforce best practices for data modeling, pipeline reliability, observability, testing, and documentation — by building the reference implementations yourself.
Optimize platform performance and manage costs across Snowflake compute, Databricks clusters, and Fabric capacities through hands-on tuning and configuration.
Implement data governance and security controls across engineering initiatives, ensuring compliance, data quality, and lineage traceability at the code and platform level.
Stay current with the evolving data platform landscape and evaluate emerging tools through hands-on proof-of-concept work, not just vendor demos.
Preferred Qualifications:
A career path that shows sustained, hands-on implementation even as responsibilities grew — architect-turned-manager, not analyst-turned-manager.
Hands-on experience building medallion-architecture lakehouses on Databricks or Microsoft Fabric, and designing and tuning performant Snowflake warehouse structures.
Experience implementing CI/CD for data pipelines using Azure DevOps or GitHub Actions, including writing the pipeline definitions and deployment scripts yourself.
Familiarity with dbt for transformation orchestration, with personal experience writing and maintaining dbt models and tests.
Exposure to real-time or near-real-time data ingestion patterns (Kafka, Event Hubs, Spark Structured Streaming) through direct implementation.
Experience with data mesh or domain-oriented data platform strategies is a strong plus.
Strong communication skills with the ability to articulate architectural trade-offs to both technical and non-technical audiences.
Excellent stakeholder management skills, with experience running sprint planning, design reviews, and cross-functional delivery coordination.
About Riveron:
At Riveron, we partner with clients—from global multinationals to high-growth private entities—to solve complex finance challenges, guided by our DELTA values: Drive, Excellence, Leadership, Teamwork, and Accountability. Our entrepreneurial culture thrives on collaboration, diverse perspectives, and delivering exceptional outcomes. We are committed to fostering growth, both for our clients and our people, through mentorship, integrity, and a client-centric approach. This inclusive environment offers flexibility, progressive benefits, and meaningful opportunities for impactful work that supports well-being in and out of the office.
Want to stay connected with Riveron? Join our Talent Community to learn more about our growing firm and be considered for future opportunities.
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Riveron Consulting is an Equal Opportunity Employer and believes that we are stronger together through our diversity. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, disability status, protected veteran status, sexual orientation, gender identity or any other characteristic protected by law.
Full time roles are eligible for a full range of benefits including medical, dental, and vision insurance, 401(k) with company match, and PTO. A complete description of all available benefits can be found at Riveron's Benefits page at https://riveron.com/riveron-life/. Contract roles are not eligible for benefits.
Please beware of fraudulent schemes or impersonations when going through the job application process. A Riveron employee will never recruit via text or extend unsolicited employment offers. Additionally, a Riveron employee will never ask you to exchange money or purchase anything as part of the recruiting process.
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Check AI displacement risk, transferable skills, and career alternatives for Technology and Innovation - Data Engineering Manager
The Technology and Innovation - Data Engineering Manager position at Riveron is based in India. This is an on-site position.
The Technology and Innovation - Data Engineering Manager position at Riveron is a Full time role.
The Technology and Innovation - Data Engineering Manager position at Riveron requires 7-9 yrs exp.
Key skills for the Technology and Innovation - Data Engineering Manager position at Riveron include: snowflake, sql, python, azure, dbt, git, ci/cd, github actions, kafka, ai.
