Cloud Data Engineering Manager

Overview

Design, build, and manage Azure cloud data solutions, pipelines, and governance.

Key Responsibilities

• data pipelines
• data factory
• ci/cd
• data lake
• power bi
• data governance

Tasks

-Lead the development of data pipelines and ETL/ELT workflows using Azure Data Factory, ensuring efficiency, reliability, and reusability across projects. -Provide technical mentorship and guidance to junior engineers, fostering a culture of innovation and continuous learning. -Manage CI/CD processes for data infrastructure using Azure DevOps, ARM templates, and YAML pipelines. Monitor and optimize data workloads using Azure Monitor, Log Analytics, and SQL Profiler, ensuring high availability, performance, and cost-efficiency. -Accepts tasks from management and the client. -Collaborate with data scientists, analysts, and business stakeholders to design and deliver semantic models, Power BI datasets, and dashboards that translate raw data into actionable insights. -Develop and optimize data lake and data warehouse architectures using Azure Data Lake Storage Gen2, Azure Synapse Analytics, and SQL Server to support advanced analytics and business intelligence initiatives. -Design and enforce data governance standards, metadata management, and data security policies, including row-level security and data masking using Azure Purview and SQL Server security roles. -Implement data validation and quality checks to ensure accuracy and consistency. -Design, build, and maintain scalable and secure cloud-based data solutions primarily within the Microsoft Azure ecosystem. -Work independently and with the business stakeholders to understand their requirements and drive business outcomes. -Build real-time and batch data processing solutions leveraging Azure Stream Analytics, Event Hubs, and Databricks, where applicable. -Communicates with Stakeholders. -Data Pipeline Development: Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data. Develop robust ETL (Extract, Transform, Load) processes to integrate data from diverse sources into our data ecosystem. -Implement robust data ingestion frameworks for both structured and unstructured data sources, including APIs, on-premises databases, IoT, and 3rd party systems like Workday and Procore.

Requirements

• azure
• power bi
• t‑sql
• data modeling
• sql server
• 7 years

What You Bring

-Solid understanding of data concepts, including ODS, data warehousing, and data storage. -Experience in implementing data modeling best practices (star/snowflake schema), dimensional modeling, and snapshotting techniques. -Proven experience in building enterprise-grade solutions on Azure, including: Azure Data Factory for orchestration, Azure Synapse and SQL Server for data warehousing, Azure Data Lake Storage Gen2 for scalable storage, and Azure Functions and Logic Apps for automation. -Experience using aggregate functions. -Ability to think strategically about design and architectural aspects of the data infrastructure. -Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field. -Knowledge of indexing and query optimization techniques. -Hands-on experience integrating with Microsoft Power Platform, especially Power BI, including DAX, M language, and dataset optimization. -Understanding of database normalization principles. -Strong expertise in T-SQL, including writing optimized queries, stored procedures, and views for high-performance analytics. -Proficiency with joins and subqueries. -Experience with data governance and compliance, including data lineage, audit trails, sensitive data classification, and GDPR/CCPA requirements using Azure Purview or similar tools. -7 years of professional experience in data engineering, with at least 3 years focused on Microsoft cloud data technologies. -Familiarity with referential integrity best practices. -Experienced in SQL Server Database Administration, the utilization of SQL Server database for backend development and integration services, and possessing advanced SQL concepts. -Familiarity with Agile/Scrum methodologies, source control via Git, and project management tools like Azure Boards or Jira.

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