Data Engineer (Snowflake Migration)

Mphasis

United States

12 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 Data Analysis Business Logic Batch Processing Big Data Databases Continuous Integration Data Validation Information Engineering Extract Transform Load (ETL)

+21 more

Data Warehousing Github Python (Programming Language) Microsoft SQL Server Oracle (Applications) Oracle SQL Developer Performance Tuning Query Optimization SQL Stored Procedures SQL Server Integration Services Data Processing Data Ingestion Informatica Powercenter Snowflake Integration Frameworks Data Management Cloudwatch Data Pipelines Legacy Systems Jenkins Control M

Job description

We are looking for an experienced Lead Data Engineer to support a large-scale Data Warehouse modernization and migration initiative. The ideal candidate will analyze existing ETL processes built on SSIS, Informatica, SQL Server Stored Procedures, and Oracle PL/SQL packages, understand the underlying business logic, and migrate them to Snowflake SQL and Python-based data processing frameworks.

This role requires strong expertise in Snowflake, Python, AWS, Control-M, GitHub, Jenkins, SSIS, Informatica, Oracle PL/SQL, SQL Server.. In addition to migration activities, the candidate will be responsible for data validation, report adoption support, and decommissioning legacy ETL processes.

Key Responsibilities:

Analyze and understand existing ETL and database processes built using:
SSIS
Informatica
SQL Server Stored Procedures
Oracle PL/SQL Packages

Convert and optimize existing business logic into Snowflake SQL.

Develop and maintain Python-based data ingestion and orchestration processes.

Build scalable data pipelines and batch processing solutions.

Configure, schedule, monitor, and troubleshoot jobs using Control-M.

Work with AWS services including EC2, S3, AWS Batch, Secrets Manager, and CloudWatch/Log Monitoring.

Perform Snowflake performance tuning and query optimization.

Execute data validation and reconciliation between legacy systems and Snowflake.

Partner with Reporting and Analytics teams to validate reports and ensure successful adoption of migrated data.

Support UAT, parallel runs, and production cutovers.

Decommission legacy ETL jobs, scheduling processes, and obsolete data platforms after successful migration.

Manage source code using GitHub and support CI/CD deployments through Jenkins.

Requirements

Must Have:

10+ years of Data Engineering, ETL, and Data Warehouse experience.
Strong Snowflake SQL development and performance tuning experience.
Experience migrating ETL processes from SSIS, Informatica, SQL Server, or Oracle environments.
Strong Python development skills.
Hands-on experience with Control-M scheduling and monitoring.
AWS experience with:
EC2
S3
AWS Batch
Secrets Manager
CloudWatch