Role Summary

The Manager Data Engineer acts as the technical authority within the offshore delivery team, setting strategic direction for complex data engineering solutions and overseeing mission-critical data pipelines across large-scale media and datasets. This role is responsible for architecting, optimizing, and governing advanced data platforms, while mentoring engineers and collaborating closely with US onshore leadership to deliver enterprise-grade, scalable solutions. The position demands exceptional technical acumen in Azure Data Factory (ADF) and Azure T-SQL, with a focus on innovation, automation, and operational excellence.

Key Responsibilities:

· Design, develop, and optimize enterprise ETL/ELT pipelines utilizing Azure Data Factory, Azure Data Lake Storage, and advanced serverless technologies—ensuring cross-platform scalability, security, and reliability.

· Implement highly efficient, complex SQL solutions—including advanced query optimization, partitioning, and indexing—to power sophisticated analytics models and enable real-time data processing.

· Lead the development and integration of robust automation frameworks using Python, and API orchestration, introducing innovative solutions to streamline the entire data lifecycle and maximize, operational efficiency.

· Exercise full ownership of production pipeline reliability; proactively identify and resolve critical issues through deep root-cause analysis, and institute resilient, long-term stability measures for continuous uptime.

· Establish, refine, and enforce rigorous coding and architectural standards through comprehensive code reviews and technical audits, setting quality benchmarks for the offshore engineering team.

· Champion best-in-class documentation, data lineage, and automated CI/CD deployment practices, ensuring transparency, auditability, and governance across all data assets.

· Demonstrate expert-level support for analytics and media teams, translating business challenges into scalable, high-performance technical solutions, leveraging deep Azure and SQL expertise.

Senior-Level Expectations:

· Act as the organization’s subject matter expert (SME) in end-to-end pipeline architecture, orchestration frameworks, schema evolution, and advanced Azure Data Factory strategies.

· Lead modernization initiatives across the organization, championing the adoption of technologies such as Databricks, DBT and advanced DevOps practices to future-proof the data platform and enable rapid innovation.

· Ensure strict adherence to SLAs and regulatory compliance through advanced monitoring, proactive risk mitigation, and continuous improvement of operational processes.

Required Skills

• 3-4 years of progressive experience in data engineering, with expert-level mastery of Azure Data Factory, SQL, and cloud data platforms (A zure and/or GCP).

• Proven expertise in designing, optimizing, and managing large-scale, production-grade data pipelines, including deep skills in SQL performance tuning, ADF orchestration, and CI/CD automation.

• Advanced knowledge of production operations, troubleshooting, and high-availability data processing at scale.

Good to Have

• Adverity

• Dataflow

• Big Query

• Databricks

• DBT

• Terraform

• Wrike/Jira/Azure DevOps

• DP‑203 / GCP Data Engineer certifications