The Advanced Analytics Developer (Python) is an individual contributor responsible for building and operating Python solutions that automate repeatable analytics workflows and produce advanced analytical outputs used in stakeholder reporting and Power BI dashboards. This role works alongside Power BI Developers owning the automation and analytics backbone (data shaping, QC, comparisons, forecasting/anomaly signals where applicable, APIs, scheduling, and alerting) that enables reliable, repeatable business outputs.
Role Purpose
Deliver dependable Python automation and advanced analytics that support out reporting products reducing manual effort, increasing data quality, and improving insight timeliness. Emphasize maintainable code, defensible logic, controlled execution, monitoring, and repeatable outputs.
RESPONSIBILITIES
Essential Functions
A) Python Automation Development
• Design, develop, test, and maintain Python scripts that automate repeatable analytics and reporting workflows supporting Power BI dashboards and operational reporting deliverables.
• Build modular, reusable components (functions, libraries, packages) to standardize common tasks across multiple products.
• Develop scripts that transform raw data into business-ready outputs (formatted workbooks/files, standardized extracts) with consistent logic and formatting.
B) Data Processing & Engineering Support
• Implement data transformation logic (reading from databases/files, cleaning, reshaping, joins, aggregations).
• Partner with data team to align outputs with approved datasets, definitions, and upstream constraints.
• Optimize code paths for performance and scalability when processing large datasets.
C) Automated Quality Control & Validation
• Build automated quality checks to validate completeness, accuracy, anomalies, and metric reconciliation prior to publishing outputs or dashboard refresh.
• Develop comparison/variance logic to detect changes between versions/runs and surface meaningful deltas for review.
• Implement robust error handling to fail safely, produce clear diagnostics, and reduce operational fire drills.
D) Advanced Analytics Development
• Develop analytical routines that go beyond automation, such as statistical summaries, trend decomposition, outlier/anomaly identification, driver segmentation, and forecasting outputs when required by shared projects.
• Create repeatable “analytics pipelines” that produce model-ready tables/features or analytic outputs that can be consumed in Power BI dashboards (e.g., forecast values, anomaly flags, scenario inputs, or explanatory breakdowns).
• Ensure advanced analytics logic is transparent and defensible: document assumptions, inputs, limitations, and validation checks.
E) Scheduling, Execution, and Operational Reliability
• Productionize automations via scheduled execution where applicable (parameterization, repeatable runs, run-history tracking).
• Implement logging, run status reporting, and alerting/notifications to ensure transparent operations and quick issue triage.
• Support secure execution patterns (service accounts where required, least-privilege access) and collaborate with platform owners for environment configuration.
F) Integrations (APIs / Workflow Tools / Reporting Enablement)
• Build and maintain integrations via APIs when required to automate data movement, refresh triggers, artifact generation, or export processes.
• Integrate Python automation with approved workflow tools for controlled publishing and operational handoffs.
• Ensure integration code follows security and governance expectations (controlled access, credential handling, auditability).
G) Documentation, Standards, and Maintainability
• Document automation and analytics design, inputs/outputs, dependencies, run instructions, and troubleshooting steps.
• Maintain code repositories with version control practices and clear change notes.
• Create runbooks for operational handoffs and ensure another developer can support the automation if needed.
• Support dashboard development by delivering clean, well-defined analytical outputs and validation signals the BI layer can consume and explain.
• Participate in stakeholder discussions as needed to clarify analytical requirements and acceptance criteria.
Location- Kochi (Hybrid)
Notice Period- Immediate to within 30 Days