Job Description: Core Technical Skills

- Strong Python programming experience
- Advanced SQL
- DBT development
- Google BigQuery
- PySpark
- Data engineering and ETL/ELT pipeline development
- Data validation and reconciliation
- Data migration experience

Python Libraries & Frameworks

- Pandas
- NumPy
- PyArrow
- Pytest
- Excellent Expectations or similar data quality framework
- Google Cloud Python SDK

GCP Services

- BigQuery
- Cloud Storage
- Cloud Composer / Airflow
- Dataproc
- Dataflow
- IAM
- Cloud Logging and Monitoring

Responsibilities: SAS Migration & Code Conversion

- Analyse existing SAS datasets, SAS programs, PROC SQL, Data Steps, and SAS macros.
- Convert SAS business logic into Python, SQL, PySpark, and DBT models.
- Support migration of historical and incremental SAS data into GCP.
- Document SAS-to-GCP transformation logic and technical conversion rules.
- Assist in identifying reusable patterns for SAS macro conversion.

Python Data Engineering

- Develop Python-based data processing, automation, and validation scripts.
- Build reusable Python frameworks for data ingestion, transformation, and reconciliation.
- Use Python libraries such as Pandas, NumPy, PyArrow, and Google Cloud SDK.
- Automate data quality checks, file processing, metadata extraction, and exception reporting.
- Develop utilities to compare SAS outputs with GCP outputs.





DBT & BigQuery Development

- Develop and maintain DBT models for transformation logic.
- Convert SAS PROC SQL logic into DBT SQL models.
- Implement DBT tests for data quality, uniqueness, referential integrity, and business rules.
- Support Bronze, Silver, and Gold layer implementation in BigQuery.
- Optimize SQL queries and BigQuery tables for performance and cost efficiency.

GCP Data Pipeline Development

- Build scalable data pipelines using GCP services such as:
- BigQuery
- Cloud Storage
- Cloud Composer / Airflow
- Dataproc
- Dataflow
- Cloud Functions

- Develop batch and incremental data processing workflows.
- Support orchestration, monitoring, and production deployment of pipelines.
- Implement secure data movement from legacy SAS platforms to GCP.

Data Quality, Validation & Reconciliation

- Perform source-to-target reconciliation between SAS and GCP.
- Validate record counts, financial totals, business rules, and derived metrics.
- Investigate and resolve data mismatches and transformation defects.
- Build automated reconciliation reports using Python and SQL.
- Support SIT, UAT, regression testing, and production validation.

Qualifications: Graduate in Computer Science, Data Science, or related field. 2-3 years of experience in data engineering or related field.

📌 Assistant Manager (Pune)
🏢 EXL Service
📍 Pune