Assistant Manager

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