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Assistant Manager

exl Service.com (India) Private Limited
Bengaluru, IND
Full-time
Manager · 2–3 years experience
Hybrid
Discovered 3 weeks ago

Full Job Posting

Qualifications

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

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

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