Data Analytics 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 Analytics Engineer.

Project Summary We are seeking an experienced Analytic Engineer as part of our Global H&B Data and Analytics Platform. In this role, you will apply data science principles with the technical and architectural expertise of a data engineer. This role will be focused on building robust and scalable data workflows and products, within the semantic layer, to help business stakeholders and analytic teams make data-driven decisions.

Key Responsibilities

Partner with business stakeholders and cross-functional teams to define business goals, KPIs, metrics, and ensure data assets support analysis and decision-making. Work with data scientists, actuaries and other analytical colleagues to collect and clean data for analysis Design, develop, and maintain semantic-layer data products, including analytical datasets, data models, storage structures, and Power BI-ready semantic models.

Design, develop, and optimize scalable, reusable, and governed data pipelines using Databricks and Py. Spark. Create and maintain data storage systems within the semantic layer Develop and maintain documentation for all data products Design Gold-layer analytical datasets for reporting. Troubleshoot production data quality issues.

Create Power BI-ready semantic models. Required For This Opportunity University or college degree in Computer Science, Information Systems, Mathematics, Engineering, Statistics, or related field of study. Proficiency in a modern data technology stack (e.g. Databricks, Azure: Synapse, Fabric, etc.) Strong understanding in Apache Spark or other big data frameworks (e.

g. Hadoop); distributed computing experience a plus Advanced SQL skills and experience with relational databases and database design Intermediate to Advanced level in Python; working knowledge within Py. Spark a plus Strong proficiency in data pipeline and workflow management tools (e.g. Airflow, ADF) Strong analytical skills and experience with data modeling Strong project management and organizational skills Proven ability to work independently, collaborate across teams, and manage multiple priorities.

Strong stakeholder communication skills with demonstrated ability to translate business requirements into technical solutions and maintain effective documentation and governance standards.