Work Schedule
Other
Environmental Conditions
Office
Job Description
Position Summary:
The Sr BA/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.
