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 PySpark.
• 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 PySpark 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.