**Role & seniority: ** Senior Automation Engineer

**Stack/tools: **

**Top 3 responsibilities: **

Implement cloud platform regression pipelines on GCP using Workflows/Build/Scheduler with services like BigQuery and Cloud Run.
Build Python/SQL automation for large-scale transactional reconciliation and near real-time data availability validation.
Apply data quality validations across multiple data layers to ensure system stability; support ETL/data transformations and CI/CD.

**Must-have skills: **

GCP regression implementation (Workflows, BigQuery, Cloud Run, Cloud Build, Cloud Scheduler).
Strong Python and SQL proficiency for reconciliation/validation workflows.
Working knowledge of data warehousing, ETL, transformations, and CI/CD.

**Nice-to-haves: **

Hands-on Neo4j experience with Cypher.
Proven regression work on high-volume transactional data with data quality outcomes and stability checks.

**Location & work type: ** Not specified in the provided text.

Full Description

Job description: Sr Automation Engineer with GCP , Python & SQ

JD for Sr Automation Engineer with Python & SQL - We are looking for a skilled candidate experienced in:

· Implementing cloud platform regression, preferably on GCP using Workflows, BigQuery, Cloud Run, Cloud Build, and Cloud Scheduler.
· Experience working with graph databases, preferably Neo4j, with hands‑on knowledge of the Cypher query language.
· Skilled in implementing regression for high‑volume transactional data across multiple data layers, ensuring validations for accurate data quality outcomes and system stability.
· High proficiency in Python and SQL, including the use of related libraries to automate large‑scale transactional reconciliation and validate data availability for near real‑time data.
· Good understanding of data warehousing, ETL processes, data transformations, and CI/CD deployments.

Must Have

Implementing cloud platform regression, preferably on GCP using Workflows, BigQuery, Cloud Run, Cloud Build, and Cloud Scheduler.
High proficiency in Python and SQL, including the use of related libraries to automate large‑scale transactional reconciliation and validate data availability for near real‑time data.
Good understanding of data warehousing, ETL processes, data transformations, and CI/CD deployments.

Nice to Have

Experience working with graph databases, preferably Neo4j, with hands‑on knowledge of the Cypher query language.
Skilled in implementing regression for high‑volume transactional data across multiple data layers, ensuring validations for accurate data quality outcomes and system stability.