Senior Data Engineer

Job Title :

Lead Data Engineer – SnapLogic

Location : Remote

Experience : 8+ years (with 3+ years in SnapLogic ETL)

Employment Type : Full-time

Role Overview : We are seeking a

Lead Data Engineer – SnapLogic

to design, build, and optimize data integration pipelines across on-premise and cloud platforms. The ideal candidate will have hands-on experience with

SnapLogic ETL , strong proficiency in

Oracle SQL & PL / SQL , and solid working knowledge of

Python

for automation and transformation tasks. This role requires technical leadership, collaboration with cross-functional teams, and the ability to design scalable data integration solutions.

Key Responsibilities :

Design and develop

robust, reusable, and scalable

ETL pipelines

using

SnapLogic

for data ingestion, transformation, and loading.

Integrate

data from multiple sources (databases, APIs, cloud applications) into enterprise data platforms or data warehouses.

Develop and optimize

complex SQL & PL / SQL scripts

for data extraction, transformation, and validation.

Implement

data quality, validation, and error-handling mechanisms

within SnapLogic pipelines.

Use

Python

for automation, data manipulation, and advanced transformation logic when required.

Collaborate with business analysts, data architects, and other engineers to translate business requirements into technical designs.

Lead code reviews, enforce best practices, and mentor junior data engineers.

Work closely with the

Cloud

and

DevOps

teams to deploy and monitor ETL pipelines in

AWS

environments.

Ensure

data security, performance tuning, and compliance

with enterprise data governance standards.

Monitor and troubleshoot data pipeline failures using SnapLogic dashboards, logs, and alerting mechanisms.

Primary Skills : SnapLogic ETL :

End-to-end pipeline development, Snap configuration, account management, error handling, and scheduling.

Oracle SQL & PL / SQL :

Advanced query optimization, stored procedures, functions, and performance tuning.

Python :

Data processing, scripting for automation, and integration support within ETL workflows.

Good to Have Skills :

AWS Cloud competency :

Experience with S3, Redshift, Lambda, and Glue.

DevOps & CI / CD :

Familiarity with Git, Jenkins, or automated deployment of SnapLogic pipelines.

Data Warehousing Concepts :

Dimensional modeling, star / snowflake schema design.

API Integration :

Experience with REST / SOAP Snaps or API-based data sources.