Job Title: Data Engineer /Analytics Engineer
Summary: We are seeking a skilled Analytics Engineer to design, build, and optimize scalable data models and analytics solutions. This role bridges data engineering and business intelligence, enabling high-quality, reliable datasets and driving consistent, trusted insights across the organization.
Job Description :-
| Company: | Convera |
| Job Role: | Data Engineer |
| Batches: | 2022-2026 |
| Degree: | Bachelor’s degree |
| Experience: | Freshers/Experienced |
| Location: | Pune, India |
| CTC/Salary: | INR 6-10 LPA (Expected) |
Key Responsibilities:
Data Modeling in Snowflake
• Design and maintain analytics-ready data models in Snowflake
• Implement star and snowflake schemas optimized for BI consumption
• Build fact, dimension, and aggregate tables for reporting and KPIs
• Apply medallion architecture (staging → intermediate → marts)
• Optimize warehouse performance using clustering, pruning, and proper SQL patterns
Analytics Engineering with dbt
• Develop and maintain dbt models for transforming raw data into curated datasets
• Write modular, reusable SQL using dbt best practices
• Implement dbt tests (not null, unique, relationships, custom tests)
• Create and maintain dbt documentation, including model descriptions and lineage
• Use dbt snapshots for slowly changing dimensions (SCD Type 2)
• Manage environments (dev / staging / prod) using dbt Cloud or dbt Core
Metrics & Semantic Layer Enablement
• Define business metrics and KPIs using dbt models and metric layers
• Ensure consistent metric definitions across Tableau dashboards
• Partner with stakeholders to validate KPI logic and assumptions
• Reduce metric duplication and reporting discrepancies
Tableau Enablement & BI Optimization
• Publish and maintain certified Tableau data sources
• Design Tableau-friendly data models to improve dashboard performance
• Optimize Snowflake queries for Tableau extracts and live connections
• Support Tableau developers by providing trusted datasets and guidance
• Troubleshoot dashboard performance and data accuracy issues
Data Quality, Testing & Observability
• Proactively monitor data freshness and accuracy
• Investigate and resolve data quality issues impacting dashboards
• Implement data validation checks using dbt tests and Snowflake queries
• Support incident response for data-related issues
Orchestration & CI/CD
• Schedule and orchestrate dbt runs using dbt Cloud or Airflow
• Use Git for version control and code reviews
• Implement CI/CD pipelines for dbt deployments
• Enforce coding standards and peer review processes
Governance, Security & Compliance
• Implement role-based access control (RBAC) in Snowflake
• Ensure sensitive data is handled per governance and compliance standards
• Maintain clear ownership and documentation for datasets
• Support audit and data lineage requirements
Collaboration & Stakeholder Engagement
• Partner with Data Engineers on ingestion and upstream dependencies
• Work closely with Analysts, Product, and Business teams to translate requirements
• Enable self-service analytics through well-documented data assets
• Provide mentorship and SQL/dbt best practices to analytics users
Required Skills & Experience (Typical)
• Strong SQL expertise with Snowflake
• Hands-on experience with dbt (Core or Cloud)
• Experience supporting Tableau dashboards and data sources
• Knowledge of dimensional modeling and analytics best practices
• Familiarity with Git-based workflows and CI/CD
• Understanding of cloud data platforms (AWS preferred)
Data & Analytics Expertise
- Strong understanding of analytics engineering principles
- Experience defining and managing business metrics (KPIs) and semantic layers
- Ability to translate business requirements into scalable and reusable data models
Data Governance & Quality
- Understanding of data governance, lineage, and security best practices
- Experience implementing role-based access control (RBAC) and handling sensitive data
- Strong focus on data accuracy, consistency, and observability
Nice-to-Have
• Experience with FinTech / Banking data
• Exposure to data observability tools (Monte Carlo, Elementary, Datadog)
• Experience defining enterprise KPIs and semantic layers
Soft Skills
• Strong problem-solving and debugging skills
• Ability to work independently in complex environments
• Excellent communication with both technical and non-technical teams
• Ownership mindset for production data pipelines.
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