While the position covers a broad range of analytics activities, it requires someone who can efficiently help the ML team source, prepare, and optimize data from our systems for their use cases—in addition to supporting wider business intelligence needs. Experience with data warehousing, workflow orchestration tools (such as Airflow), Azure Functions, and Feature Store concepts will be highly valued. The ideal candidate can communicate complex data findings clearly and has a deep understanding of database structures and optimization techniques.

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Key Responsibilities

Data Analysis & Exploration

· Extract, transform, and analyze complex datasets to uncover patterns and insights.

· Perform statistical analysis to identify trends, correlations, and anomalies.

· Collaborate with stakeholders—including ML engineers—to understand business questions and provide data-driven solutions.

· Create comprehensive reports explaining data findings and their business implications.

SQL Development & Database Management

· Write and optimize complex SQL queries for data extraction and analysis.

· Design efficient database queries with a focus on performance and scalability.

· Implement query refactoring techniques to improve execution time and resource usage.

· Understand and work with database schemas, stored procedures, and views.

Data Visualization & Reporting

· Design and develop interactive dashboards and reports using Power BI.

· Create visually compelling and insightful data visualizations that tell a story.

· Present analytical findings to technical and non-technical stakeholders.

· Maintain and improve existing dashboards and reporting solutions.

Support for AI/ML Initiatives

· Prepare, clean, and preprocess data for machine learning models.

· Assist in designing and implementing ETL pipelines for AI/ML workflows.

· Support ML engineers with feature engineering and, where applicable, Feature Store management.

· Schedule and monitor data workflows using tools such as Airflow or Azure Functions.

· Validate and analyze model outputs and performance metrics in partnership with the ML team.

Data Quality & Governance

· Identify and address data quality issues.

· Document data sources, transformations, and analysis methodologies.

· Ensure data accuracy and reliability in reports, dashboards, and ML datasets.

· Adhere to data governance policies and best practices.

Key Skills & Technologies

SQL & Databases:

· Advanced Microsoft SQL Server, T-SQL, performance tuning, database design

Python Stack:

· Pandas, NumPy, Matplotlib, Seaborn, SciPy, Statsmodels, Jupyter

Visualization:

· Power BI (required), Tableau (preferred), strong dashboard design skills

ETL & Automation:

· Data cleaning, ETL pipelines, automation scripts

· Workflow orchestration (Apache Airflow)

· Azure Functions for automated data tasks

Other Tools & Knowledge:

· Git, Excel (advanced), statistical analysis, data modeling

· Data warehousing concepts (Azure Synapse, Snowflake, etc.)

· Feature Store familiarity is a plus

Required Qualifications

· Bachelor's degree in computer science, Statistics, Mathematics, or related field.

· 2–3 years of experience in data analysis roles.

· Strong proficiency in SQL, particularly T-SQL with Microsoft SQL Server.

· Experience with Python data analysis libraries (Pandas, NumPy, Matplotlib, etc.).

· Proven experience creating dashboards and visualizations with Power BI.

· Excellent analytical and problem-solving skills.

· Strong communication skills with the ability to translate complex findings into business insights.

· Experience working with large datasets and optimizing query performance.

Nice to Have

· Experience supporting ML/AI teams with data preparation and model evaluation.

· Knowledge of cloud data platforms (Azure preferred, AWS).

· Experience with data modeling and dimensional modeling concepts.

· Certifications in data analysis, SQL, or visualization tools.

· Experience with Azure Data Factory or other ETL tools.

· Familiarity with version control and collaborative development practices.

Why Join Us?

· Opportunity to work with diverse and complex datasets.

· Collaborative environment with exposure to cutting-edge AI/ML technologies.

· Projects that have a direct impact on business decisions.

· Career growth path into advanced analytics, data engineering, or data science.

· Competitive compensation and benefits package.

· Professional development opportunities and continuous learning culture.

Industry

• Software Development

Employment Type

F