Senior Data Engineer (Dataform, BigQuery) at AI Industry · Mumbai, Bengaluru (Bangalore), Hyderabad, Gurugram · 6 - 10 years · ₹32L - ₹42L / yr · Posted 26 Mar 2026
Amazon Web Services (AWS)
PythonRole & Responsibilities:
We are looking for a strong Data Engineer to join our growing team. The ideal candidate brings solid ETL fundamentals, hands-on pipeline experience, and cloud platform proficiency — with a preference for GCP / BigQuery expertise.
Responsibilities:
- Design, build, and maintain scalable data pipelines and ETL/ELT workflows
- Work with Dataform or DBT to implement transformation logic and data models
- Develop and optimize data solutions on GCP (BigQuery, GCS) or AWS/Azure
- Support data migration initiatives and data mesh architecture patterns
- Collaborate with analysts, scientists, and business stakeholders to deliver reliable data products
- Apply data governance and quality best practices across the data lifecycle
- Troubleshoot pipeline issues and drive proactive monitoring and resolution
Ideal Candidate:
- Strong Data Engineer Profile
- Must have 6+ years of hands-on experience in Data Engineering, with strong ownership of end-to-end data pipeline development.
- Must have strong experience in ETL/ELT pipeline design, transformation logic, and data workflow orchestration.
- Must have hands-on experience with any one of the following: Dataform, dbt, or BigQuery, with practical exposure to data transformation, modeling, or cloud data warehousing.
- Must have working experience on any cloud platform: GCP (preferred), AWS, or Azure, including object storage (GCS, S3, ADLS).
- Must have strong SQL skills with experience in writing complex queries and optimizing performance.
- Must have programming experience in Python and/or SQL for data processing.
- Must have experience in building and maintaining scalable data pipelines and troubleshooting data issues.
- Exposure to data migration projects and/or data mesh architecture concepts.
- Experience with Spark / PySpark or large-scale data processing frameworks.
- Experience working in product-based companies or data-driven environments.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
NOTE:
- There will be an interview drive scheduled on 28th and 29th March 2026, and if shortlisted, they will be expected to be available on these Interview dates. Only Immediate joiners are considered.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Python- Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.
- Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).
- Work with cloud platforms GCP, Azure to manage data infrastructure.
- GCP as mandatory skills
- Collaborate with analytics and product teams to understand data needs and deliver solutions.
- Ensure data quality, reliability, security, and compliance across all data systems.
- Mentor junior data engineers and contribute to best practices and code reviews.
- Monitor and troubleshoot data pipeline performance and resolve data-related issues.
- Automate data validation, monitoring, and alerting processes.
- 8+ years of experience in data engineering or software engineering with a data focus.
- Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
- Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
- Strong understanding of data modeling, data lakes, and ETL/ELT design.
- Hands-on experience with orchestration tools like Airflow, dbt, or similar.
- Solid experience with cloud data platforms (AWS/GCP/Azure).
- Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).
- Experience working in a DevOps or DataOps environment.
- Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).
- Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).
- Experience supporting machine learning workflows and data science initiatives.
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
What you'll need
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
- 5+ years of professional data engineering experience.
- Experience designing and building cloud-native data solutions.
- Strong expertise with Google Cloud Platform, including BigQuery. Experience developing transformation frameworks using dbt.
- Strong SQL and Python programming skills.
- Experience with PostgreSQL or other relational databases.
- Experience orchestrating workflows using Apache Airflow or Cloud Composer.
- Experience implementing Infrastructure as Code using Terraform. Experience building CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar platforms.
- Experience developing scalable batch and streaming data pipelines. Strong problem-solving skills with the ability to balance scalability, reliability, and cloud cost optimization.
Preferred Qualifications
- Experience with Pub/Sub, Datastream, Dataflow, Cloud Storage, Cloud Functions, or Cloud Run.
- Experience building multi-tenant SaaS platforms.
- Experience implementing metadata-driven governance, lineage, and data quality frameworks.
- Experience supporting AI, machine learning, or customer-facing analytics platforms.
- Experience with Kubernetes and Docker.
PythonJob Summary
Role Overview
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.
Experience with Google Cloud Platform (GCP) will be an added advantage.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
- Develop complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain reliable data integration workflows across multiple data sources.
- Perform data cleansing, validation, transformation, and quality checks.
- Analyze data and provide insights to support business and technical requirements.
- Implement and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
- Troubleshoot data pipeline failures, performance issues, and production incidents.
- Optimize data processing workflows for performance, scalability, and reliability.
- Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
- Follow best practices for version control, testing, documentation, and deployment.
- Contribute to cloud-based data engineering initiatives, preferably on GCP.
Required Skills
- 5–7 years of hands-on experience in Data Engineering.
- Strong programming skills in Python.
- Strong expertise in Advanced SQL and database concepts.
- Hands-on experience with ETL/ELT processes and data pipelines.
- Good understanding of Data Warehousing and Data Modeling concepts.
- Experience with CI/CD practices and tools.
- Strong understanding of DevOps principles, automation, and deployment processes.
- Strong data analytics and problem-solving skills.
- Experience working with large datasets and performance optimization.
- Good understanding of Git/version control and software development best practices.
Good to Have
- Hands-on experience with Google Cloud Platform (GCP).
- Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
- Experience with containerization/orchestration technologies such as Docker/Kubernetes.
- Experience with workflow orchestration tools such as Airflow.
- Knowledge of cloud-based data architecture and distributed data processing.
Preferred Candidate Profile
- Strong analytical and problem-solving abilities.
- Good communication and stakeholder management skills.
- Ability to work independently as well as in a collaborative team environment.
- Strong ownership of data pipelines and production systems.
- Candidates who can join at short notice are preferred.
Mandatory Skills
Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops
Kubernetes
ScalaDescription
We are looking for Senior Data Engineers to join our AdTech team and build scalable, high-performance data platforms that power advertising insights and analytics. The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Spark and Scala.
You will work on designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL pipelines for large-scale data processing.
- Build and optimize distributed data applications using Spark and Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Work with large datasets to ensure data quality, consistency, and performance.
- Collaborate with engineering, product, and analytics teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, and cost efficiency.
- Deploy and manage data workloads in cloud and containerized environments.
- Troubleshoot production issues and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering or Big Data Engineering.
- Strong hands-on experience with Apache Spark and Scala.
- Experience building and maintaining ETL pipelines.
- Familiarity with Google Cloud Storage (GCS).
- Experience with Kubernetes (K8s).
- Strong SQL skills and understanding of distributed data processing.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with AWS and cloud-native data services.
- Familiarity with streaming technologies such as Kafka.
- Experience working on large-scale data platforms or AdTech systems.
- Exposure to orchestration tools such as Airflow.
Benefits
- Best-in-class salary: We hire strong talent and compensate accordingly.
- Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
- Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
- High-impact work: Build AI-first systems and products used at scale by global clients.
About Us
Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.
Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.
PythonAmazon Web Services (AWS)Skills Referential (Required knowledge, skills and abilities)
Technical Skills:
Python
Pyspark
SQL
ETL Aws, Azure, gcp
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,
PythonRole Overview
We are looking for a GCP Data Engineer with 10+ years of experience to design, develop, and optimize scalable cloud-based data solutions. The ideal candidate will have strong hands-on expertise in GCP, BigQuery, and advanced SQL, with experience building data pipelines and working with large-scale datasets.
Key Responsibilities
- Design and develop scalable data pipelines and ETL/ELT processes on GCP.
- Build, optimize, and maintain data solutions using Google BigQuery.
- Develop complex SQL queries for data transformation, aggregation, and analysis.
- Design efficient data models and optimize pipelines for performance, scalability, and cost.
- Integrate data from multiple sources and ensure data quality, reliability, and availability.
- Troubleshoot pipeline and data issues and drive continuous improvement.
- Collaborate with data architects, analysts, application teams, and business stakeholders.
- Follow best practices for cloud security, data governance, testing, and documentation.
Required Skills
- 8+ years of Data Engineering experience
- Strong hands-on experience with GCP, Django, and MongoDB
- Extensive experience with BigQuery
- Advanced SQL skills
- Strong understanding of ETL/ELT and data pipeline development
- Data modeling and data warehousing experience
- Experience handling large-scale datasets and performance optimization
- Strong problem-solving and communication skills
Good to Have
- GCP services such as Cloud Storage, Dataflow, Pub/Sub, Cloud Composer, or Cloud Functions
- Python or other data engineering languages
- Experience with data governance and security
- Agile development experience
Python🚨 Hiring: GCP Data Engineer
We are looking for experienced GCP Data Engineers to join our team!
🔹 Experience: 9+ Years
🔹 Relevant Experience: 4+ Years in GCP Data Engineering
🔹 Required Skills: GCP, Oracle PL/SQL, Python, PySpark
🔹 Location: Bangalore / Hyderabad
🔹 Notice Period: Immediate to 10 Days Preferred
Key Skills:
🔹 Strong hands-on experience in GCP Data Engineering
🔹 Good experience with PySpark & Python
🔹 Strong knowledge of Oracle PL/SQL
🔹 Experience in data processing, ETL, and data pipelines
🔹 Good understanding of cloud-based data engineering
📩 Interested candidates can share their updated CV via DM.
#Hiring #GCPDataEngineer #GCP #DataEngineering #PySpark #Python #OraclePLSQL #DataEngineer #BangaloreJobs #HyderabadJobs #ImmediateJoiner #TechJobs #ITJobs #HiringNow
Job Description
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Develop data processing solutions using Python.
- Write complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain data ingestion and integration workflows.
- Implement data quality, validation, monitoring, and error-handling processes.
- Develop and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
- Collaborate with data analysts, data scientists, software engineers, and business teams.
- Optimize data pipelines for performance, reliability, and scalability.
- Troubleshoot production data issues and ensure timely resolution.
- Follow best practices for version control, code quality, testing, and deployment.
Mandatory Skills
- Python
- ETL
- SQL
- CI/CD
- DevOps
- Git / Version Control
- Strong problem-solving and debugging skills
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon