Lead Data Engineer

Accenture in India; Ernakulam; On-site; INR 1,500,000 - 3,400,000; Full time

Job summary

Accenture in India seeks a Lead Data Engineer specializing in GCP and BigQuery. With 5+ years of data engineering experience, you will design and optimize scalable data pipelines and analytics solutions on Google Cloud.

You will collaborate with architects, data scientists, and analysts to deliver production-grade data platforms, drive cost efficiency, and ensure data quality across ETL/ELT workflows and real-time processing.

Qualifications

• 5+ years of experience in data engineering and cloud-based data platforms.
• Strong hands-on experience with BigQuery, Python, SQL, Cloud Storage and Dataflow.
• Familiar with ETL/ELT, data warehouses, data lake concepts and data modeling.
• Graduation is required.

Responsibilities

• Design, develop and optimize scalable data pipelines using BigQuery, Dataflow, Pub/Sub, Dataproc, and Cloud Composer.
• Independently design and deliver production-grade data solutions, improving performance and cost efficiency.
• Collaborate with architects, data scientists, analysts and stakeholders to translate requirements into scalable tech.
• Build data models, partitioning, and datasets for analytics and reporting workloads on GCP.
• Implement data validation, quality checks, monitoring, and security controls in production pipelines.
• Provide guidance on modern GCP data architecture and best practices across the team.
• Orchestrate batch and streaming pipelines using Cloud Composer and related services.

Skills

GCP services

BigQuery

Python

SQL

Education

Graduation

Tools

BI

Analytical Tool

Job description

Job Title - Lead Data Engineer – Specialist - ACS SONG
Management Level: Level 9 - Specialist
Location: Kochi, Coimbatore, Trivandrum
Must have skills: GCP services, BigQuery, Python, and SQL.
Good to have skills: BI and Analytical Tool
Experience: 5 -8 years of experience is required
Educational Qualification: Graduation
Job Summary
We are seeking a Lead Data Engineer specializing in Google Cloud Platform (GCP) and BigQuery with 5+ years of experience in data engineering, cloud-based data platforms, data pipelines, SQL development, and large-scale data processing. The role will focus on designing, developing, and optimizing scalable data pipelines and analytics solutions using BigQuery and other GCP data services.
Roles And Responsibilities

• The ideal candidate should have strong hands‑on experience with BigQuery, Python, SQL, Cloud Storage, Dataflow, Pub/Sub, Dataproc, and Cloud Composer, along with a solid understanding of ETL/ELT, data warehouse, data lake, and modern cloud data architecture principles.
• This position requires the ability to independently design and deliver production‑grade data solutions, optimize performance and cost, troubleshoot complex data issues, and collaborate closely with architects, data scientists, analysts, application teams, and business stakeholders.
• Design, develop, and maintain scalable data pipelines and data processing solutions using GCP services, BigQuery, Python, and SQL.
• Build reliable and high‑performance data transformation and integration workflows supporting reporting, analytics, machine learning, and downstream business applications.
• Drive improvements in data quality, pipeline performance, BigQuery optimization, cost efficiency, monitoring, security, and production stability.
• Provide technical guidance and contribute to the adoption of modern GCP data engineering architecture, standards, and development best practices.
• Design, develop, and maintain batch and real‑time data pipelines using BigQuery, Cloud Storage, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Python, and SQL.
• Develop ETL/ELT solutions for ingesting, transforming, and integrating structured, semi‑structured, and unstructured data from multiple source systems.
• Design and maintain scalable BigQuery datasets, tables, views, materialized views, partitioning, clustering, and data models for analytics and reporting workloads.
• Optimize BigQuery SQL queries, storage structures, data processing workloads, and pipeline architecture to improve performance and control cloud consumption costs.
• Build and maintain batch and streaming data processing solutions using services such as Dataflow, Pub/Sub, Dataproc, and BigQuery.
• Design curated data layers, reusable datasets, and data models supporting enterprise analytics, BI, machine learning, and downstream applications.
• Implement data validation, reconciliation, data quality checks, error handling, lineage, monitoring, alerting, and operational controls.
• Orchestrate data pipelines and workflows using Cloud Composer / Apache Airflow, Workflows, or equivalent orchestration technologies.
• Collaborate with solution architects, data architects, data scientists, analysts, application teams, and business stakeholders to translate requirements into scalable technical solutions.
• Follow and promote engineering best practices covering Git‑based development, automated testing, CI/CD, Infrastructure as Code, documentation, monitoring, security, and production support.