GCP Senior Data Engineer at Xebia IT Architects · Bengaluru (Bangalore), Gurugram, Pune, Hyderabad, Chennai, Bhopal, Jaipur · 10 - 15 years · ₹30L - ₹40L / yr · Profitable · Posted 17 May 2025
Python
We are looking for a Senior Data Engineer with strong expertise in GCP, Databricks, and Airflow to design and implement a GCP Cloud Native Data Processing Framework. The ideal candidate will work on building scalable data pipelines and help migrate existing workloads to a modern framework.
- Shift: 2 PM 11 PM
- Work Mode: Hybrid (3 days a week) across Xebia locations
- Notice Period: Immediate joiners or those with a notice period of up to 30 days
Key Responsibilities:
- Design and implement a GCP Native Data Processing Framework leveraging Spark and GCP Cloud Services.
- Develop and maintain data pipelines using Databricks and Airflow for transforming Raw → Silver → Gold data layers.
- Ensure data integrity, consistency, and availability across all systems.
- Collaborate with data engineers, analysts, and stakeholders to optimize performance.
- Document standards and best practices for data engineering workflows.
Required Experience:
- 7-8 years of experience in data engineering, architecture, and pipeline development.
- Strong knowledge of GCP, Databricks, PySpark, and BigQuery.
- Experience with Orchestration tools like Airflow, Dagster, or GCP equivalents.
- Understanding of Data Lake table formats (Delta, Iceberg, etc.).
- Proficiency in Python for scripting and automation.
- Strong problem-solving skills and collaborative mindset.
⚠️ Please apply only if you have not applied recently or are not currently in the interview process for any open roles at Xebia.
Looking forward to your response!
Best regards,
Vijay S
Assistant Manager - TAG
Shubham Vishwakarma
Full Stack Developer - Averlon
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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.
PythonAbout the Role
We are looking for a Senior Data Engineer with strong hands-on expertise in Databricks, Python, PySpark, and SQL to build scalable, high-performance data engineering solutions. You’ll architect and develop large scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems. Databricks is the core enterprise data and processing platform for this role. You will also use Apache Airflow for workflow orchestration and dbt for ELT transformations, and will contribute to designing reliable, secure, and governed data platforms that enable analytics, reporting, and AI-driven use cases.
Key Responsibilities
- Design and implement large-scale data pipelines using Python/PySpark, Databricks, and Microsoft Fabric.
- Develop and optimize data processing workloads in Databricks using PySpark and Spark SQL, with a strong focus on scalability, reliability, performance, and maintainability.
- Develop and maintain dbt models including layered architecture, incremental models, snapshots, macros, testing, and documentation.
- Design, develop, and maintain Apache Airflow DAGs for orchestrating reliable, scalable, and observable data pipelines.
- Design and implement data quality, observability, and governance frameworks, including automated testing, monitoring, lineage, access control, and data privacy standards.
- Partner with analytics, product, and business stakeholders to turn requirements into trustworthy datasets, and raise the engineering bar through design discussions, code reviews, and mentoring junior engineers.
Required Skills
- Strong expertise in Python for developing scalable, modular, and production-ready data engineering applications.
- Strong expertise in PySpark, including DataFrame API, Spark SQL, Structured Streaming, partitioning strategies, joins, caching, handling data skew, and Spark performance optimization.
- Strong hands-on experience with Databricks for data ingestion, transformation, processing, and optimization, including Delta Lake, Unity Catalog, Databricks Workflows, notebooks, jobs, and Databricks-native data engineering capabilities.
- Strong experience in Databricks/Spark performance tuning, including query and job optimization, partitioning, file sizing, caching, join optimization, handling data skew, and efficient use of compute resources.
- Hands-on experience with Delta Lake, including transactional data processing, schema management, incremental data processing, and reliable batch and streaming data pipelines.
- Hands-on experience in developing dbt projects using layered architecture, incremental models, snapshots, macros/Jinja, testing, documentation, and deployment best practices.
- Expertise in advanced SQL and data modelling — dimensional modeling, slowly changing dimensions, schema evolution, and query optimization.
- Hands-on experience in developing and managing Apache Airflow DAGs, scheduling workflows, dependency management, retries, backfills, and operational monitoring.
- Hands-on experience with at least one major cloud platform (AWS, Azure or GCP).
- Strong problem-solving skills and the ability to work independently with business and analytics stakeholders.
Nice to Have
- Hands-on exposure to Microsoft Fabric for data integration and analytics.
- Experience using AI coding assistants (e.g. Claude Code, GitHub Copilot) as part of a development workflow.
- Familiarity with modern DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and containerization (Docker/Kubernetes).
- Domain expertise in financial services.
PythonJob Description – Senior GCP Data Engineer
Position: Senior GCP Data Engineer
Experience: 8+ Years
Budget: Up to 30 LPA
Location: Bangalore / Hyderabad
Relocation: Candidates from Chennai / Pune willing to relocate are also welcome.
Notice Period: Immediate to 15 Days
Interview Process:
- Round 1: Virtual Interview
- Round 2 / DM Round: Face-to-Face Interview
Required Skills
- Strong hands-on experience in GCP Data Engineering.
- Good programming experience in Python.
- Strong experience with PySpark / Apache Spark.
- Proficiency in SQL and database concepts.
- Experience in developing and maintaining data pipelines.
- Good understanding of data processing, transformation, and integration.
- Experience in handling large-scale data processing.
- Strong problem-solving and debugging skills.
- Good understanding of cloud-based data engineering concepts.
- Experience in optimizing data pipelines for performance and scalability.
Preferred Skills
- Previous experience in a Lead Data Engineer role.
- Experience in technical leadership, mentoring, and guiding team members.
- Ability to collaborate with cross-functional teams and deliver data engineering solutions.
Roles & Responsibilities
- Design, develop, and maintain scalable data pipelines using GCP.
- Develop data processing and transformation workflows using Python and PySpark.
- Write and optimize SQL queries for efficient data processing.
- Build and maintain reliable data engineering solutions.
- Troubleshoot data pipeline issues and optimize performance.
- Ensure data quality, reliability, and scalability.
- Collaborate with stakeholders and team members to deliver project requirements.
- Lead and guide team members where applicable.
- Important: Candidates must have strong Senior Data Engineer experience. Lead experience is preferred but not mandatory.
PythonGCP 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
PythonGCP Data engineer (L1 virtual, L2 or DM F2F )
GCP + Python + Pyspark + sql + Lead
8+yrs
Bangalore/hyderabad location ( relocation profiles also from Chennai pune location)
immediate to 15days
Python🚀 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.
PythonExperience: 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.
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
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Senior Data Engineer – Ab Initio | GCP | Spark | Agentic AI
Location: Bangalore
Experience: 5+ Years
Role: Senior Data Engineer
Work Mode: Bangalore
Job Summary
We are looking for an experienced Senior Data Engineer with strong expertise in Ab Initio, GCP, Apache Spark, and Agentic AI. The ideal candidate will have hands-on experience designing and developing scalable data engineering solutions, building data pipelines, and working with modern cloud and AI technologies.
The candidate should be comfortable working across traditional enterprise data platforms and emerging Generative AI / Agentic AI solutions.
Key Responsibilities
- Design, develop, and maintain scalable and high-performance data pipelines using Ab Initio, Spark, and GCP services.
- Develop and optimize complex ETL/ELT workflows using Ab Initio.
- Build and maintain data processing solutions using Apache Spark / PySpark.
- Develop cloud-based data solutions on Google Cloud Platform (GCP).
- Work with GCP data services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, or equivalent services.
- Perform data integration, transformation, cleansing, and validation.
- Optimize data pipelines for performance, scalability, reliability, and cost.
- Collaborate with data architects,
PythonExperience: 6+ years overall Data Engineering experience.
Must-have — candidates should have hands-on experience in ALL of these:
- GCP (Google Cloud Platform) – strong hands-on experience
- Python – data engineering/ETL development
- SQL – advanced SQL, query optimization, data transformation
- BigQuery – strong hands-on experience with development, optimization and data warehousing
- Data Engineering / ETL – building and maintaining data pipelines
- GCP data services – preferably Cloud Storage, Dataflow, Pub/Sub, Composer/Airflow, etc.
- Data warehousing / dimensional modeling
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon