GCP Data Engineer
At a glance
Mid-level Data Engineering role at Fa Ewjt Saasfaprod1. Hyderabad · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Review SAS datasets, ETL jobs and macros, then recreate their transformation logic in DBT and GCP pipelines
- Build modular ELT workflows in DBT and BigQuery for ingesting, transforming and aggregating data
- Check SAS-to-GCP results, trace data mismatches and support automated pipeline tests and monitoring
- Tune BigQuery and SQL workloads, while documenting data lineage and metadata
- Work with architecture, analysis, modeling and QA teams on reviews and planning; mentor junior engineers
What you bring
- A degree in computer science, data science or a related subject
- Four to six years working in data engineering or a related area
Who this fits
This mid-level Hyderabad role suits someone with data engineering experience who can handle SAS migration alongside DBT and GCP pipeline development. The position is hybrid.
From the employer
Core Technologies
- DBT (Data Build Tool)
- Google BigQuery
- SQL
- Python
- PySpark
- Git
GCP Services
- BigQuery
- Cloud Storage
- Dataproc
- Cloud Composer (Airflow)
- Dataflow
- IAM
SAS Technologies
- SAS Base
- SAS Enterprise Guide
- PROC SQL
- SAS Macros
- SAS Data Sets
Data Engineering
- ETL / ELT Development
- Data Warehousing
- Data Pipeline Design
- Performance Optimization
- Data Validation & Reconciliation
Data Modeling
- Star Schema
- Snowflake Schema
- Dimensional Modeling
- Source-to-Target Mapping
SAS Migration & Modernization
- Analyze existing SAS datasets, ETL jobs, PROC SQL code, and SAS macros.
- Convert SAS transformation logic into DBT models and cloud-native data pipelines.
- Support migration of historical and incremental data from SAS platforms to GCP.
- Participate in migration assessments, code conversion, and reconciliation activities.
Data Engineering & Development
- Design and develop scalable ELT pipelines using DBT and BigQuery.
- Build and optimize data ingestion, transformation, and aggregation processes.
- Develop reusable and modular DBT models following best practices.
- Implement performance tuning for SQL and BigQuery workloads.
- Create and maintain data lineage and metadata documentation.
Data Quality & Reconciliation
- Design and implement data quality validation frameworks.
- Perform source-to-target reconciliation between SAS and GCP platforms.
- Investigate and resolve data inconsistencies and migration issues.
- Support automated testing and monitoring of data pipelines.
Cloud Platform Development
- Build and manage solutions using:
- BigQuery
- Cloud Storage
- Dataproc
- Cloud Composer (Airflow)
- Dataflow
- Support data security, access controls, and governance requirements.
Collaboration & Delivery
- Work closely with Data Architects, Business Analysts, Data Modelers, and QA teams.
- Participate in design reviews and sprint planning sessions.
- Estimate effort and provide technical input during project planning.
- Mentor junior engineers and enforce engineering best practices.
Graduate in Computer Science, Data Science, or related field. 4-6 years of experience in data engineering or related field.
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