Key Responsibilities

Data Engineering

•       Design, develop, and maintain robust ETL/ELT pipelines to ingest data from diverse sources (APIs, databases, flat files, SaaS platforms).

•       Build and optimize data models, data warehouses, and data lakes to support analytics and reporting needs.

•       Ensure data quality, integrity, and availability through monitoring, validation, and automated testing.

•       Implement best practices for data governance, security, and compliance (e.g., GDPR, role-based access).

•       Optimize SQL queries, stored procedures, and pipeline performance for large-scale datasets.

•       Collaborate with analytics and BI teams to deliver clean, well-documented, and reliable datasets.

Power Automate & Workflow Automation

•       Design and implement automated workflows using Microsoft Power Automate (Cloud Flows, Desktop Flows, and Process Mining).

•       Integrate Power Automate with Microsoft 365, SharePoint, Dataverse, Power BI, Azure services, and third-party APIs.

•       Build RPA solutions to automate repetitive manual tasks and reduce operational overhead.

•       Develop reusable connectors, custom connectors, and solution packages following ALM best practices.

•       Monitor flow performance, troubleshoot failures, and implement error-handling and retry logic.

•       Partner with business users to identify automation opportunities and translate requirements into scalable solutions.

Collaboration & Delivery

•       Document data pipelines, automation flows, and architectural decisions clearly.

•       Participate in code reviews, sprint planning, and Agile ceremonies.

•       Mentor junior engineers and contribute to engineering standards and reusable assets.

•       Stay current with emerging technologies in the Microsoft data and Power Platform ecosystem.

Required Qualifications

•       Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.

•       3+ years of experience as a Data Engineer or in a similar data-focused role.

•       Strong proficiency in SQL and at least one programming language (Python preferred; Scala or Java acceptable).

•       Hands-on experience building ETL/ELT pipelines using tools such as Azure Data Factory, SSIS, dbt, Databricks, or Apache Airflow.

•       Experience with cloud data platforms (Azure Synapse, Snowflake, AWS Redshift, BigQuery, or similar).

•       Solid understanding of data modeling concepts (star/snowflake schemas, normalization, dimensional modeling).

•       Demonstrated experience designing and deploying Power Automate flows in a production environment.

•       Familiarity with the broader Microsoft Power Platform (Power Apps, Power BI, Dataverse).

•       Working knowledge of REST APIs, JSON, and authentication patterns (OAuth, service principals).

•       Experience with version control (Git) and CI/CD practices.