Analytics Engineer Duties and Responsibilities

- Contribute to the design and development of scalable reporting and analytics solutions that enable trusted business metrics and self-service reporting.
- Design and build data solutions using Databricks, SQL, Python, Spark, and Delta Lake within the Azure ecosystem (Blob Storage, Data Factory, Event Hubs).
- Develop, maintain, and optimize complex SQL queries, views, stored procedures, and reporting datasets supporting enterprise reporting platforms such as SSRS and Tableau.
- Design and implement dimensional data models, including fact and dimension tables, to support reporting, analytics, and KPI standardization.
- Collaborate with business stakeholders to understand reporting requirements and translate them into scalable data and reporting solutions.
- Support existing reporting solutions by troubleshooting production issues, implementing enhancements, and developing new reports, datasets, and data products.
- Participate in defining and standardizing business KPIs, metrics, and reporting logic across the organization.
- Contribute to the development of reusable transformation and semantic layers using up-to-date analytics engineering practices (dbt or equivalent frameworks).
- Adhere to best practices for ETL/ELT development, including data quality, testing, maintainability, performance optimization, and reusability.
- Collaborate with engineers, product teams, and business leaders to ensure data platforms integrate effectively with reporting tools, APIs, and custom applications.
- Establish and follow CI/CD processes, testing frameworks, infrastructure-as-code practices, and monitoring solutions using Git, Terraform, Azure DevOps, GitHub Actions, Jenkins, Azure Monitor, or similar technologies.
- Support modernization initiatives including reporting platform upgrades, BI tool migrations, and analytics platform enhancements.
- Adhere to organizational security, compliance, and governance standards.

Qualifications Education
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field,



or equivalent professional experience.
- Advanced degree is a plus.

Experience
- 5+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or Data Warehousing.
- Strong experience with Microsoft SQL Server, PostgreSQL, MySQL, or similar relational database platforms.
- Hands-on experience developing and optimizing complex SQL queries, stored procedures, and reporting datasets.
- Experience supporting enterprise reporting platforms such as SSRS, Tableau, Power BI, or similar BI tools.
- Experience designing dimensional data models using Kimball methodology, including fact tables and dimension tables.
- Experience working directly with business users to gather requirements and deliver reporting and analytics solutions.
- Experience with Databricks, Delta Lake, and up-to-date cloud-based data platforms.
- Experience with Azure data services such as Data Factory, Blob Storage, Synapse Analytics, and Event Hubs.
- Exposure to analytics engineering concepts, semantic layers, metrics frameworks, or dbt is highly desirable.
- Experience in healthcare, revenue cycle management, or other regulated industries is a plus.

Specific Job Knowledge, Skills, and Abilities
- Strong T-SQL development skills, including query optimization, execution plan analysis, indexing strategies, and stored procedure tuning.
- Strong programming skills in Python, Scala, or Java, with experience using PySpark, Pandas, or related frameworks.
- Robust understanding of data warehousing concepts, dimensional modeling, and analytics data architecture.
- Understanding of KPI frameworks, metrics definitions, semantic layers, and reusable reporting datasets.
- Experience with Databricks notebooks, Delta Lake, Unity Catalog, and modern ELT architectures.
- Familiarity with Git, CI/CD practices, Azure DevOps, GitHub Actions, or similar tooling.
- Ability to balance new development, operational support, and continuous improvement initiatives.
- Excellent communication and stakeholder management skills.
- Strong analytical and problem-solving abilities with a focus on delivering business value through data.

📌 Data Engineer (India)
🏢 LogixHealth
📍 India