Data Engineer

Data Engineer

Experience - 5+ years

6-7 LPA

Remote

Duration: 1 month contract (We can take as a tentative, It can be extended)

Scope: Subscriber Activation, Churn, FTE and future reporting requirements, with BigQuery as the centralized data warehouse and Power BI as the proposed reporting layer.

Key Skills:

Strong hands-on experience with GCP & BigQuery

Data warehouse architecture, design and implementation

Data ingestion/integration across multiple source systems

ETL/ELT and data pipeline development

Data modelling for reporting and analytics

Experience integrating BigQuery with Power BI or similar reporting tools

Experience: 6+ years overall Data Engineering experience.

Must-have — candidates should have hands-on experience in ALL of these:

1. GCP (Google Cloud Platform) – strong hands-on experience
2. Python – data engineering/ETL development
3. SQL – advanced SQL, query optimization, data transformation
4. BigQuery – strong hands-on experience with development, optimization and data warehousing
5. Data Engineering / ETL – building and maintaining data pipelines
6. GCP data services – preferably Cloud Storage, Dataflow, Pub/Sub, Composer/Airflow, etc.
7. Data warehousing / dimensional modeling

GCP Data Engineer

Job Description

Experience: 4-10 Years Location: Bangalore, India Employment:

Role Overview

We are seeking a GCP Data Engineer to design, build and maintain data systems on Google Cloud Platform. The role focuses on building pipelines with BigQuery, Dataflow and Pub/Sub, managing cloud storage, and enabling real-time data processing for fast, reliable analytics.

Key Responsibilities

• Design, develop and maintain scalable batch and real-time data pipelines on GCP.

• Build ETL/ELT pipelines with rollback strategies, bad-record handling and performance optimization.

• Design end-to-end data integration flows across systems.

• Design scalable fact/dimension schemas in cloud data warehouses.

• Handle structured, semi-structured and unstructured data at scale.

• Implement data quality checks, security and compliance policies; protect sensitive information.

• Optimize data systems by identifying bottlenecks, tuning queries and adopting new technologies.

• Collaborate with data scientists, analysts and business stakeholders to deliver tailored data solutions.

Technical Skills

• GCP Services: Cloud Run functions, Cloud Scheduler, Workflows, Pub/Sub, GCS, Dataflow, BigQuery, Cloud Build.

• Programming: Strong SQL / PL-SQL, Python and object-oriented languages (Java, Python); API development.

• CI/CD: Deployment using GitHub Actions and Jenkins.

• Data Modelling: Top-down and bottom-up database design, data masking, normalization, denormalization, dimensional modeling.

• Big Data & Streaming: Streaming architectures, NoSQL stores and key-value databases under high concurrency and volume.

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering or a related field.

• 4-10 years of data engineering experience with hands-on GCP delivery.

• Strong problem-solving, communication and stakeholder management skills.

• GCP Professional Data Engineer certification preferred.

Sourcing Preference

• Priority 1: Internal profiles (TCSers).

• Priority 2: If no suitable internal profile is identified, external candidates available for immediate joining.

Desirable Skills:

Keyword:

Skills: Digital : Python~Digital : NOSQL~Digital : Google Cloud

Experience Required: 6-8

Job Title: GCP Data Engineer

Experience: 6–8 years

Location : Bangalore

What are they looking for?

They need a Google Cloud Platform (GCP) Data Engineer who can build and maintain data pipelines, process large volumes of data, and manage data storage using Google Cloud services.

The candidate should have hands-on experience with batch and real-time data processing, ETL workflows, and cloud data warehousing.

Mandatory / Core Skills

• Google Cloud Platform (GCP)
• Google Cloud Dataflow
• Pub/Sub
• Apache Beam
• BigQuery
• Cloud Storage / Bigtable
• Cloud Composer (Apache Airflow)
• ETL / data pipeline development
• Apache Spark / Hadoop using Dataproc

Supporting Skills

• Cloud Data Fusion
• NoSQL databases
• Data quality and governance
• Data security, access controls, and encryption
• Batch and real-time streaming
• Preparing datasets for BI, analytics, and machine learning

Job Summary

We are seeking a highly skilled GCP Data Engineer with strong expertise in Google Cloud Platform (GCP), Python, ETL, and modern data engineering technologies. The ideal candidate should have hands-on experience designing and building scalable data pipelines using BigQuery, Dataflow, Pub/Sub, Airflow, and modern data lake technologies such as Apache Iceberg or Delta Lake.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines on Google Cloud Platform.
• Build and optimize data processing workflows using Python and Google Cloud Dataflow (Apache Beam).
• Develop and manage large-scale analytical data models in BigQuery.
• Implement event-driven data ingestion using Google Cloud Pub/Sub.
• Create, schedule, and monitor workflows using Apache Airflow and Autosys.
• Design and implement modern data lake architectures using Apache Iceberg or Delta Lake.
• Optimize query performance, storage, and compute costs in GCP.
• Ensure data quality, governance, security, and compliance across data platforms.
• Collaborate with Data Scientists, Analysts, and Application teams to deliver scalable data solutions.
• Troubleshoot production issues and continuously improve pipeline reliability and performance.

Mandatory Skills

• Strong hands-on experience with Google Cloud Platform (GCP).
• Proficiency in Python programming.
• Experience in designing and implementing ETL/ELT pipelines.
• Strong knowledge of BigQuery.
• Experience with Google Cloud Dataflow (Apache Beam).
• Experience with Google Cloud Pub/Sub.
• Hands-on experience with Apache Airflow.
• Experience in job scheduling using Autosys.
• Experience with modern table formats such as Apache Iceberg or Delta Lake.
• Strong SQL and data modeling skills.

Preferred Skills

• Experience with Cloud Storage, Dataproc, Cloud Composer, and Cloud Functions.
• Knowledge of CI/CD pipelines and DevOps practices.
• Experience with Docker and Kubernetes.
• Familiarity with Git and Agile/Scrum methodologies.
• Knowledge of data warehousing and dimensional modeling.
• Exposure to streaming and real-time data processing.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
• 4–8+ years of experience in Data Engineering with hands-on expertise in GCP technologies.

Required Experience

• Strong experience in developing enterprise-grade data pipelines using Python and GCP.
• Hands-on experience with BigQuery, Dataflow, Pub/Sub, and Airflow.
• Experience scheduling and monitoring batch workflows using Autosys.
• Experience implementing modern data lake architectures using Apache Iceberg or Delta Lake.
• Strong understanding of ETL best practices, performance tuning, and data optimization.
• Excellent analytical, troubleshooting, and problem-solving skills.

Mandatory Skills

• Google Cloud Platform (GCP)
• Python
• ETL
• BigQuery
• Autosys
• Apache Airflow
• Google Cloud Pub/Sub
• Google Cloud Dataflow (Apache Beam)
• Apache Iceberg / Delta Lake
• SQL & Data Modeling

GCP Data Engineer

Job Description

Experience: 4-10 Years Location: Bangalore, India Employment:

Role Overview

We are seeking a GCP Data Engineer to design, build and maintain data systems on Google Cloud Platform. The role focuses on building pipelines with BigQuery, Dataflow and Pub/Sub, managing cloud storage, and enabling real-time data processing for fast, reliable analytics.

Key Responsibilities

• Design, develop and maintain scalable batch and real-time data pipelines on GCP.

• Build ETL/ELT pipelines with rollback strategies, bad-record handling and performance optimization.

• Design end-to-end data integration flows across systems.

• Design scalable fact/dimension schemas in cloud data warehouses.

• Handle structured, semi-structured and unstructured data at scale.

• Implement data quality checks, security and compliance policies; protect sensitive information.

• Optimize data systems by identifying bottlenecks, tuning queries and adopting new technologies.

• Collaborate with data scientists, analysts and business stakeholders to deliver tailored data solutions.

Technical Skills

• GCP Services: Cloud Run functions, Cloud Scheduler, Workflows, Pub/Sub, GCS, Dataflow, BigQuery, Cloud Build.

• Programming: Strong SQL / PL-SQL, Python and object-oriented languages (Java, Python); API development.

• CI/CD: Deployment using GitHub Actions and Jenkins.

• Data Modelling: Top-down and bottom-up database design, data masking, normalization, denormalization, dimensional modeling.

• Big Data & Streaming: Streaming architectures, NoSQL stores and key-value databases under high concurrency and volume.

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering or a related field.

• 4-10 years of data engineering experience with hands-on GCP delivery.

• Strong problem-solving, communication and stakeholder management skills.

• GCP Professional Data Engineer certification preferred.

Sourcing Preference

• Priority 1: Internal profiles (TCSers).

• Priority 2: If no suitable internal profile is identified, external candidates available for immediate joining.

Desirable Skills:

Keyword:

Skills: Digital : Python~Digital : NOSQL~Digital : Google Cloud

Experience Required: 6-8

Experience: 5+ Years

Employment Type: Full-Time

Role Overview

We are looking for an experienced GCP Data Engineer with 5+ years of experience in data engineering and strong hands-on expertise in Google BigQuery, Google Cloud Storage (GCS), Airflow/Cloud Composer, Python, and Vertex AI. The candidate should be capable of designing, developing, and maintaining scalable data pipelines and cloud-based data solutions on Google Cloud Platform.

Key Skills – Mandatory

• BigQuery – Strong hands-on experience in data warehousing, SQL, optimization, and performance tuning.
• Google Cloud Storage (GCS) – Experience with data storage, file management, and integration with data pipelines.
• Airflow / Cloud Composer – Experience in developing, scheduling, monitoring, and managing data workflows.
• Python – Strong programming skills for data engineering, ETL/ELT development, automation, and pipeline implementation.
• Vertex AI – Experience working with ML/AI workflows, model integration, or data pipelines supporting AI/ML solutions.

Good to Have / Added Advantage

• Dataproc – Experience with distributed data processing and Spark-based workloads.
• Cloud Data Fusion – Experience in building and managing data integration pipelines.
• Cloud Run – Understanding of deploying and running containerized applications/services on GCP.
• Experience with ETL/ELT processes and data pipeline development.
• Knowledge of GCP data architecture and cloud-native services.
• Experience in data quality, validation, monitoring, and troubleshooting.

Responsibilities

• Design, develop, and maintain scalable GCP-based data pipelines.
• Build and optimize data solutions using BigQuery and Cloud Storage.
• Develop and manage workflows using Airflow / Cloud Composer.
• Write efficient and reusable Python code for data processing and automation.
• Support Vertex AI integrations and AI/ML data workflows.
• Monitor pipeline performance and troubleshoot data processing issues.
• Work with cross-functional teams to understand data requirements and deliver reliable solutions.
• Implement best practices for data security, quality, scalability, and performance.

You must have :

• 5+ years of overall experience in Data Engineering.
• Strong hands-on experience with BigQuery, GCS, Airflow/Cloud Composer, Python, and Vertex AI.
• Strong understanding of data engineering concepts, ETL/ELT, data pipelines, and cloud technologies.
• Dataproc, Data Fusion, and Cloud Run experience will be an added advantage.

🚀 Hiring: Senior GCP Data Engineer

We are looking for experienced Senior Data Engineers with strong hands-on expertise in Google Cloud Platform (GCP), Python, PySpark, and SQL. Candidates with team lead experience will be preferred.

📌 Job Details:

• Role: Senior GCP Data Engineer
• Experience: 8+ Years
• Budget: Up to ₹30 LPA
• Location: Bangalore / Hyderabad
• Relocation: Candidates from Chennai and Pune willing to relocate are welcome.
• Notice Period: Immediate to 15 days
• Interview Process: L1 – Virtual | L2 / DM – Face-to-Face (F2F)

💻 Required Technical Skills:

• Strong hands-on experience with GCP data engineering.
• Excellent proficiency in Python, PySpark, and SQL.
• Experience in designing, developing, and optimizing data pipelines.
• Good understanding of ETL/ELT processes and large-scale data processing.
• Experience working with cloud-based data platforms and data warehousing.
• Strong analytical, problem-solving, and communication skills.

⭐ Preferred Skills:

• Previous experience as a Technical Lead or leading a data engineering team.
• Knowledge of GCP services such as BigQuery, Dataproc, Dataflow, and Cloud Storage.

GCP Data engineer

Exp 9+yrs

Bangalore/Hyderabad

Lead exp+ Python + pyspark + sql or plsql

immediate to 15days joiners

Call or WhatsApp: 6 3 8 5 0 7 6 1 4 2

Job Title : Senior Data Engineer – GCP & Apache Spark

Job Details :

• Number of Positions : 3
• Employment Type : Contract-to-Hire (C2H)
• Experience Required : 5 to 8 Years
• Location : Manyata Tech Park, Bengaluru
• Work Mode : Hybrid – 3 Days in Office per Week
• Preferred Notice Period : Immediate to 15–20 Days
• Project Duration : Initially 6–8 months, with a strong possibility of extension for long-term projects
• Relocation : Candidates from outside Bengaluru can apply if they are willing to relocate.

Role Overview :

We are looking for experienced Senior Data Engineers with strong expertise in Google Cloud Platform (GCP), Apache Spark, BigQuery, and SQL to design, develop, and maintain scalable data pipelines and distributed data processing solutions.

The ideal candidate should have hands-on experience with cloud-based data engineering, end-to-end pipeline architecture, system design, performance optimization, debugging, and CI/CD practices.

Mandatory skills :

Apache Spark (PySpark / Scala), SQL, GCP, BigQuery, GCP Dataproc, Data Pipelines, System Design, CI/CD, Debugging & Problem-Solving.

Key Responsibilities :

• Design, develop, and maintain scalable data pipelines using Apache Spark, PySpark, and/or Scala.
• Build and optimize batch and distributed data processing workflows on GCP.
• Work extensively with BigQuery for data transformation, validation, analytics, and query optimization.
• Develop and maintain data workflows using GCP services, including Dataproc, BigQuery, and Cloud Storage.
• Design end-to-end data pipeline architectures with a focus on scalability, reliability, and performance.
• Write and optimize complex SQL queries for large-scale datasets.
• Troubleshoot and resolve data processing issues, pipeline failures, and performance bottlenecks.
• Implement CI/CD practices for data engineering workflows, testing, and deployments.
• Monitor pipeline performance and identify opportunities for continuous improvement.
• Collaborate with cross-functional teams to understand requirements and deliver reliable data solutions.
• Participate in code reviews, testing, production deployments, and production support.

Mandatory Skills :

• Strong hands-on experience with Apache Spark, including PySpark and/or Scala.
• Strong SQL skills and experience working with large-scale datasets.
• Hands-on experience with Google Cloud Platform (GCP).
• Practical experience with BigQuery and data warehousing concepts.
• Working knowledge of GCP Dataproc.
• Strong understanding of data pipelines, end-to-end workflows, and system design.
• Practical experience with CI/CD and deployment processes.
• Excellent debugging, troubleshooting, and problem-solving skills.

Preferred Skills :

• Experience with Apache Airflow, Google Cloud Composer, or similar orchestration tools.
• Knowledge of Kafka or other streaming and messaging technologies.
• Proficiency in Python for data engineering and automation.
• Experience with Git-based development workflows.
• Knowledge of Linux/Unix environments and shell scripting.
• Familiarity with monitoring, logging, data quality, and governance practices.

Required Qualifications :

• 5 to 8 years of experience in Data Engineering, Big Data Engineering, or a related field.
• Proven experience developing and maintaining scalable data pipelines.
• Strong understanding of distributed data processing and cloud-based data architecture.
• Ability to troubleshoot complex technical issues and optimize pipeline performance.
• Strong communication, collaboration, and ownership skills.

Interview Process :

Round 1 : AI-Based Interview

• Candidates must complete the AI interview as soon as possible after receiving the invitation.

Round 2 : Virtual Interview Drive

• Interviews are planned for the upcoming drive; exact dates will be communicated separately.

Round 3 : Online Client Interview

• Shortlisted candidates will attend the online interview.
• Candidates must be available throughout the day on the scheduled interview date.