Sr BI Developer

Work Schedule

Environmental Conditions

Job Description

Position Summary:

The Sr BI Developer is responsible for designing, developing, and delivering scalable business intelligence and analytics solutions that support data-driven decision-making across services and operational domains.

This role combines strong technical expertise with functional understanding to translate business requirements into robust data models, dashboards, and insights. The position plays a key role in driving best practices, ensuring solution quality, and supporting advanced analytics initiatives aligned with enterprise data strategy.

Key Responsibilities:

Business Analysis & Requirements Management

• Engage with business stakeholders to elicit, analyze, and document detailed business and reporting requirements.
• Facilitate workshops to define KPIs, standardized metric logic, and data definitions.
• Develop functional specifications, source-to-target mappings, and technical design documentation.
• Ensure traceability from requirements through development, testing, and deployment.

BI Development & Technical Execution

• Design and develop enterprise dashboards and reports using Power BI (PBI) including advanced DAX, optimized data models, and performance tuning.
• Build and maintain SSAS tabular models and semantic layers to support enterprise analytics.
• Develop and optimize complex SQL queries within Amazon Redshift environments.
• Perform dashboard performance optimization, query tuning, and model refinement.
• Support UAT, deployment, and post-production stabilization activities.

Data Engineering & Databricks Platform Development

• Design and develop scalable data transformation workflows using the Databricks Lakehouse platform (Spark, PySpark, SQL, Delta Lake).
• Build and maintain ETL/ELT pipelines within Databricks to support BI and advanced analytics workloads.
• Implement and manage Delta Lake architecture, including partitioning strategies, performance optimization, and data version control.
• Integrate Databricks pipelines with Amazon Redshift and AWS services (S3, Glue, IAM, Lambda).
• Support ingestion of structured and semi-structured data from ERP, CRM, and service systems into curated analytical layers.
• Perform pipeline monitoring, troubleshooting, and optimization to ensure reliability and scalability.

Advanced Analytics & GenAI Enablement

• Contribute to advanced analytics initiatives including predictive metrics, anomaly detection, and automation use cases.
• Support integration of AI/ML models and Generative AI (GenAI)-enabled reporting capabilities into BI solutions.
• Explore opportunities for AI-assisted insights, natural language querying, and intelligent automation within dashboards.

Collaboration & Support

• Work closely with BI Leads, product owners, and data engineers to deliver prioritized solutions.
• Participate in production issue resolution and root cause analysis.
• Provide functional walkthroughs and technical knowledge transfer to business users.

Qualifications:

Education & Experience

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Business Analytics, or related field required.
• 8+ years of experience combining Business Analysis, BI development, and data engineering.
• Experience supporting service operations or commercial analytics domains preferred.

Skills & Knowledge

Business Analysis

• Strong requirement elicitation, documentation, and stakeholder engagement skills.
• Experience preparing functional and technical design artifacts.
• Exposure to ERP (SAP), CRM (SFDC), or service management systems.
• Experience in service domain analytics.

BI & Reporting

• Advanced expertise in Power BI (DAX, Power Query, enterprise modeling, performance optimization).
• Strong hands-on experience with SSAS tabular modeling and cube development.
• Proficiency in SQL with demonstrated experience in Amazon Redshift.

Data Engineering (Databricks-Focused)

• Strong hands-on experience with Databricks (Spark, PySpark, Delta Lake, Workflows).
• Experience designing ETL/ELT pipelines within a Lakehouse architecture.
• Working knowledge of the AWS ecosystem (S3, Redshift, Glue, IAM).
• Strong understanding of data warehousing concepts, dimensional modeling, and pipeline optimization.

Advanced Analytics

• Exposure to AI/ML fundamentals and predictive analytics concepts.
• Familiarity with Generative AI (GenAI), LLM-based analytics use cases, or AI-assisted reporting frameworks.
• Experience working in Agile/Scrum delivery environments.

• AWS, Databricks, Power BI, or AI/ML-related certifications.