Data Engineer

Xencia Technology Solutions; Bengaluru; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Xencia Technology Solutions is seeking hands-on Snowflake Data Engineers in Bengaluru/Kochi (work from office) to build and maintain data ingestion and transformation pipelines on the Snowflake Data Cloud. You will support a client in Australia, collaborating with distributed teams across time zones.

The role emphasizes reliable, performant, and cost-efficient data pipelines. Requirements include 2–3 years of Snowflake experience, strong SQL, knowledge of Snowflake features, and proficiency in

Qualifications

• Hands-on Snowflake data engineering experience.
• Strong SQL with performance tuning and advanced analytics.
• Experience with at least one ETL/ELT tool (dbt, Fivetran, Matillion, Informatica or Talend).
• Cloud platform experience (AWS/Azure/GCP) and cloud storage.
• Proficiency in Python or scripting for data processing.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines into Snowflake.
• Implement ingestion with Snowpipe, COPY INTO, and stages.
• Develop transformations using SQL/dbt across raw, staging, curated layers.
• Optimize Snowflake objects and tune warehouse performance.
• Monitor cost, credits, and compute usage; ensure reliability.
• Collaborate with distributed teams across time zones; document pipelines.

Skills

Snowflake

SQL performance

dbt

ETL/ELT tools

Snowpipe

Airflow

CI/CD

Python

Tools

dbt

Fivetran

Matillion

Informatica

Talend

Job description

Location: Bengaluru / Kochi (Work from Office)

Working Hours: 8 A.M IST – 5 P.M IST (Australia Time Zone)

Experience: 2-3 years of hands-on Snowflake experience

Role Summary

We are seeking hands-on Snowflake Data Engineers to build and maintain data ingestion and transformation pipelines on the Snowflake Data Cloud. Engineer will support a client based in Australia, collaborating with distributed teams across time zones. The role involves moving data from source systems into Snowflake, transforming it into curated, analytics-ready models, and ensuring pipelines are reliable, performant, and cost-efficient.

Key Responsibilities

• Design, build, and maintain ETL/ELT pipelines to load data into Snowflake from databases, files, APIs, and streaming feeds.
• Implement ingestion using Snowflake-native features such as Snowpipe, COPY INTO, external/internal stages, Streams, and Tasks.
• Develop transformation logic using SQL and dbt (or equivalent), following a layered architecture (raw → staging → curated / data marts).
• Build and optimise Snowflake objects: databases, schemas, tables, views, materialized views, stored procedures, and user-defined functions.
• Tune query and warehouse performance - clustering, warehouse sizing, query profiling, and caching.
• Monitor and optimise Snowflake credit/compute consumption to keep the platform cost-efficient.
• Integrate with orchestration/ingestion tools such as dbt, Fivetran, Matillion, Airflow, Informatica, or Talend as applicable.
• Implement data quality checks and robust error handling within pipelines.
• Collaborate with data architects, testers, and the client's business/BI teams to deliver requirements.
• Maintain clear documentation for pipelines, data models, and data lineage.

Required Skills

• 2-3 years of hands-on experience building data pipelines on Snowflake.
• Strong SQL - complex joins, window functions, CTEs, and performance tuning.
• Practical knowledge of Snowflake features: virtual warehouses, stages, Snowpipe, Streams, Tasks, Time Travel, cloning, and roles/RBAC.
• Experience with at least one ETL/ELT tool (dbt, Fivetran, Matillion, Informatica, Talend, or similar).
• Understanding of data warehousing and dimensional modelling concepts (star/snowflake schema, SCDs).
• Experience with at least one cloud platform (AWS, Azure, or GCP) and cloud storage (S3, Blob, GCS).
• Proficiency in Python or scripting for data processing and automation.
• Familiarity with version control (Git) and CI/CD practices.
• Good written and verbal English communication for working with a remote client.
• Ability to work independently and manage deliverables across time zones with limited overlap.

Good to Have

• Experience with semi-structured data (JSON, Parquet, Avro) using VARIANT and Snowflake's semi-structured functions.
• Exposure to data governance, masking policies, and row/column-level security.
• Experience with real-time / streaming ingestion (Kafka, Snowpipe Streaming).