Data Engineer

Why AIS? When you join AIS, you’re joining a mission-driven team that’s passionate about making a difference. You’ll work on projects that matter, alongside industry-leading experts, in an environment that fosters innovation, driving client success, and empowering our team to make a lasting impact. As an employee-owned company, we value collaboration, inclusivity, continuous growth, and shared success.

Employee Ownership : Your contributions directly impact the company’s success, and you share in its achievements. Continuous Learning : Access to resources, training, and mentorship to support your professional growth. Inclusive Culture : A workplace where diversity is celebrated, and everyone’s voice is valued. Mission-Driven Work : Engage in projects that make a meaningful difference for our clients and communities.

What are we looking for? At AIS, we're looking for more than just skills - we're looking for driven individuals who are passionate about making a difference, eager to grow, and aligned with our core principles. Working@AIS At AIS, we are dedicated to providing our employees with diverse opportunities to grow their careers while supporting a variety of impactful projects.

For this position, we are seeking a talented individual to join AIS as a Data Analytics Engineer. Core Knowledge & Skills: Writes complex SQL; models data; builds and maintains ETL/ELT pipelines; applies Python/R and BI tools; works with data warehouses and introductory cloud services; conducts intermediate statistical and ML analyses.

Work & Complexity: Designs pipelines and optimizes performance; addresses moderate data quality and integration issues; directly improves project efficiency and reliability. Quality & Independence: Produces high-quality analyses and reproducible results; operates independently within defined parameters; suggests process enhancements.

Teamwork & Communication: Partners with cross-functional teams; presents findings to stakeholders; establishes feedback loops; begins mentoring juniors. Consulting & Engagement: Consults on analytics projects, elicits needs, proposes solutions, and documents outcomes. As your initial project assignment, you will support the unique needs of our client as a Data Engineer.

Project Summary We are looking for a mid-level Data Engineer with 4-6 years of experience to build and support modern data solutions using Microsoft Fabric and the Azure data ecosystem. The role is primarily hands-on and will involve developing reliable data pipelines, transforming and modeling data for analytics, and supporting scalable lakehouse-based solutions.

The ideal candidate should have strong data engineering fundamentals, solid SQL skills, and practical experience with Microsoft Fabric.

Key Responsibilities

Build and maintain data ingestion pipelines from relational databases, APIs, files, SaaS applications, and cloud storage sources. Develop transformation workflows across Bronze, Silver, and Gold layers within Microsoft Fabric. Create curated analytical datasets and dimensional models for downstream reporting and analytics.

Implement incremental data processing, validation, error handling, and data quality checks. Develop reusable and maintainable data engineering components, including metadata-driven patterns where appropriate. Support data workloads across Fabric Lakehouse, Warehouse, Pipelines, and Notebooks Monitor and troubleshoot pipeline failures, data issues, and performance bottlenecks.

Participate in code reviews, testing, documentation, and deployment activities. Work with architects, BI developers, analysts, and source-system teams to translate business requirements into data solutions. Follow engineering standards for security, source control, CI/CD, observability, and production support . Required For This Opportunity Data Engineering, Data Platform, or BI Engineering roles.

Strong hands-on experience with SQL and relational data concepts. Practical experience with Microsoft Fabric, particularly: Data Factory / Pipelines Lakehouse One. Lake Notebooks Warehouse Experience with Spark, Py. Spark, or Spark SQL. Good understanding of Delta Lake and lakehouse architecture. Experience designing and implementing ETL/ELT and incremental data processing.

Good understanding of Medallion Architecture and layered data transformation patterns. Experience with dimensional modeling, including facts, dimensions, and star schemas. Working knowledge of Git and CI/CD practices. Good understanding of data quality, troubleshooting, logging, and production support.

Nice to Have

Skills Experience with Azure services such as Key Vault, Entra ID, and Azure DevOps. Familiarity with Power BI, Semantic Models, and Direct Lake. Experience with CDC, Change Tracking, or other incremental ingestion techniques. Familiarity with Fabric security, governance, lineage, and Microsoft Purview. Experience integrating data from platforms such as Salesforce.

Microsoft Fabric or Azure data certifications.