Job Opportunities API

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 performan