Data Engineer

HTC Global Services; Chennai District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

HTC Global Services is seeking an experienced Data Engineer with strong Python and Google Cloud Platform (GCP) expertise to design, develop, and maintain scalable data pipelines and cloud-based data solutions. The candidate will work closely with data analysts, data scientists, and business stakeholders to build reliable data platforms and enable data-driven decision-making.

The role focuses on ETL/ELT design, Python-based data processing, and orchestration with Dataflow and Cloud Composer.

Qualifications

• Experience designing scalable ETL/ELT pipelines in Python and GCP.
• Proficient in BigQuery SQL and data modeling.
• Hands-on with GCP services like Dataflow, Cloud Composer, and Cloud Storage.

Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines using Python and GCP services.
• Develop reusable Python-based data processing solutions.
• Build and manage pipelines using Dataflow, Cloud Composer, BigQuery, and Cloud Storage.
• Design data models and optimize queries in BigQuery.
• Ingest data from APIs, databases, files, and other sources.
• Implement data validation, monitoring, and error-handling mechanisms.
• Optimize pipelines for performance, scalability, reliability, and cost.
• Collaborate with stakeholders to translate data requirements into solutions.
• Implement CI/CD for data engineering solutions.
• Troubleshoot production pipelines and provide root-cause analysis.
• Ensure data security, governance, and compliance.
• Prepare technical documentation for pipelines and architecture.

Skills

Python

GCP

BigQuery

SQL

Dataflow

Airflow

ETL/ELT

CI/CD

REST APIs

Data governance

Tools

Git

Looker

Job description

We are looking for an experienced Data Engineer with strong Python and Google Cloud Platform (GCP) expertise to design, develop, and maintain scalable data pipelines and cloud-based data solutions. The candidate will work closely with data analysts, data scientists, and business stakeholders to build reliable data platforms and enable data-driven decision-making.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT data pipelines using Python and GCP services.

Develop high-quality, reusable, and efficient Python-based data processing solutions.

Build and manage data pipelines using Google Cloud Dataflow, Cloud Composer, BigQuery, and Cloud Storage.

Design data models and optimize queries and workloads in Google BigQuery.

Develop data ingestion processes from APIs, databases, files, and other data sources.

Implement data validation, quality checks, monitoring, and error-handling mechanisms.

Optimize data pipelines for performance, scalability, reliability, and cost.

Work with stakeholders to understand data requirements and translate them into technical solutions.

Implement CI/CD processes and follow DevOps best practices for data engineering solutions.

Troubleshoot production data pipeline issues and provide root-cause analysis.

Ensure data security, governance, access control, and compliance requirements are followed.

Prepare technical documentation for data pipelines, architecture, and operational processes.

Required Skills

Strong hands-on experience with Python for data engineering and automation.

Strong experience with Google Cloud Platform (GCP).

Hands-on experience with BigQuery and SQL.

Experience with Google Cloud Storage (GCS).

Experience with Cloud Composer / Apache Airflow.

Experience with Dataflow / Apache Beam.

Strong understanding of ETL/ELT concepts and data pipeline architecture.

Good knowledge of relational databases and SQL optimization.

Experience working with REST APIs and different data formats such as JSON, CSV, and Parquet.

Experience with Git and CI/CD tools.

Understanding of cloud security, IAM, and data governance.

Preferred Skills

Experience with Pub/Sub and event-driven data pipelines.

Knowledge of Cloud Functions / Cloud Run.

Experience with Dataproc / Spark.

Knowledge of data warehousing and dimensional modeling.

Experience with Terraform or other Infrastructure-as-Code tools.

Exposure to data visualization tools such as Looker or Power BI.

Experience working in Agile/Scrum environments.