Data Engineer

Shift: 2 pm 11 pm

Key Responsibilities

- Design, configure, and maintain the Snowflake platform, including databases, schemas, warehouses, roles, security policies, and environment setup across development, test, and production.

- Implement and manage cloud-based ingestion using Fivetran for legacy, operational, and SaaS source systems, including full-load, incremental, and CDC-based patterns.

- Build and optimize the target data architecture across raw, staging, curated, and reporting-ready layers, aligned to medallion-style or equivalent modular design patterns.

- Develop, test, and maintain dbt models that replace legacy SSIS transformation logic and support curated business-ready data assets for reporting, reconciliation, and analytics.

- Translate legacy constructs such as SCD Type 2 handling, lookup logic, conditional branching, and other ETL patterns into modern Snowflake and dbt implementations.

- Configure AWS integrations required for the data platform, including S3 stages, IAM roles, storage integrations, encryption support, and secure connectivity patterns.

- Establish and support source-to-target mappings, metadata consistency, schema evolution handling, and documentation of field-level lineage across ingestion and transformation layers.

- Implement automated data quality checks, freshness checks, reconciliation controls, and exception handling to improve trust in the data before it reaches reporting layers.

- Monitor ingestion pipelines, connector health, transformation runs, and Snowflake workloads; troubleshoot failures, schema drift, performance issues, and data incidents.

- Optimize Snowflake cost and performance through workload isolation, warehouse sizing, clustering, query tuning,



and platform monitoring.

- Support downstream analytics and reporting teams by delivering trusted, well-documented, analytics-ready data structures compatible with Sigma and other governed reporting tools.

- Contribute to CI/CD, release automation, and Git-based engineering workflows for dbt, Snowflake, and data pipeline changes.

- Produce operational documentation, configuration standards, runbooks, and handover materials for ongoing support and client operations teams.

- Work closely with architects, analysts, reporting teams, and client stakeholders to ensure the solution improves automation, reduces manual dependency, and supports a more scalable operating model.

Required Skills and Experience

- Strong hands-on experience implementing Snowflake in enterprise environments.

- Deep knowledge of SQL, query optimization, performance tuning, and warehouse design.

- Experience migrating from legacy EDW platforms such as SQL Server, SSIS, and SSAS.

- Familiarity with dbt, Fivetran, AWS, and BI/reporting integrations.

- Hands-on experience with Fivetran or comparable cloud ingestion tools.

- Solid AWS fundamentals: S3, IAM, KMS, VPC, PrivateLink for Snowflake connectivity

- Strong understanding of source-to-target mapping, CDC concepts, and incremental loading.

- Experience working with Snowflake and cloud-based data platforms.

- Ability to write SQL for data validation and reconciliation between source and Bronze landing tables

NICE TO HAVE

- Snowflake SnowPro Core or Advanced: Data Engineer certification

- Experience with Snowflake cost optimization on large-scale financial data workloads

- Familiarity with dbt project structure and Snowflake-specific dbt materializations (dynamic tables)

📌 Data Engineer (Bengaluru)
🏢 Xebia IT Architects
📍 Bengaluru