Data Engineer at Deqode Ā· Gurugram, Delhi, Noida, Ghaziabad, Faridabad Ā· 6 - 10 years Ā· ā¹5L - ā¹15L / yr Ā· Bootstrapped Ā· Posted 30 May 2025

š Hiring: Data Engineer | GCP + Spark + Python + .NET |
| 6ā10 Yrs | Gurugram (Hybrid)
Weāre looking for a skilled Data Engineer with strong hands-on experience in GCP, Spark-Scala, Python, and .NET.
š Location: Suncity, Sector 54, Gurugram (Hybrid ā 3 days onsite)
š¼ Experience: 6ā10 Years
ā±ļø Notice Period :- Immediate Joiner
Required Skills:
- 5+ years of experience in distributed computing (Spark) and software development.
- 3+ years of experience in Spark-Scala
- 5+ years of experience in Data Engineering.
- 5+ years of experience in Python.
- Fluency in working with databases (preferably Postgres).
- Have a sound understanding of object-oriented programming and development principles.
- Experience working in an Agile Scrum or Kanban development environment.
- Experience working with version control software (preferably Git).
- Experience with CI/CD pipelines.
- Experience with automated testing, including integration/delta, Load, and Performance

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Description
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. Weāre 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.
1st virtual , 2nd round F2FĀ -
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
Data Engineer Short Hiring Post
šØ Hiring: Data Engineer
š¹ Experience: 5ā9 Years
š¹ Location: Bangalore / Hyderabad
š¹ Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling
š¹ Process: L1 Virtual ā L2 F2F Karat Test
š¹ F2F: Bangalore / Hyderabad Location
š¹ Positions: Immediate requirement
ā ļø Note: Candidates must be available for F2F Karat immediately after L1.
#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners
We are hiring for a Data Engineer & Java scala for a full-time opportunity in Bangalore.
Experience: 4ā10 Years
Must-Have Skills:
Java / Scala / Python, Data Engineering, Databricks / Snowflake, and Cloud (AWS / Azure / GCP).
We are looking for strong software engineers with hands-on experience in data platform development, scalable backend programming, data integration, and cloud technologies.
Experience in Banking, Capital Markets, Market Risk, or Regulatory Reporting will be an added advantage.
1st virtual , 2nd round F2F
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5+yrs
Bang/hyderabad
immediate to 15days.
š 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.
š Job Details:
- Role: Senior GCP Data Engineer
- Experience: 8+ Years
- Budget: Up to ā¹30 LPA
- Location: Bangalore / Hyderabad
- Relocation: Candidates from Chennai and Pune willing to relocate are welcome.
- Notice Period: Immediate to 15 days
- Interview Process: L1 ā Virtual | L2 / DM ā Face-to-Face (F2F)
š» 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.
ā 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.
Job Title : Senior Data Engineer ā 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 ā 3 Days in Office per Week
- Preferred Notice Period : Immediate to 15ā20 Days
- Project Duration : Initially 6ā8 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
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- Candidates must be available throughout the day on the scheduled interview date.
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Description
We are looking for Senior Data Engineers to join our Data Platform team and build scalable, high-performance data platforms that power data processing, analytics, and downstream applications.
The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Apache Spark and Python Scala.
You will be responsible for 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 and data processing pipelines for large-scale datasets.
- Build and optimize distributed data applications using Apache Spark and Python Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Design and manage data workflows using Apache Airflow.
- Build and operate data workloads on AWS, with strong usage of Amazon S3 for large-scale data storage.
- Work with large datasets to ensure data quality, consistency, reliability, and performance.
- Collaborate with engineering, product, analytics, and other platform teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, performance, and cost efficiency.
- Troubleshoot production issues, identify bottlenecks, and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering, Big Data Engineering, or a similar role.
- Strong hands-on experience with Apache Spark and Scala.
- Experience designing, building, and maintaining large-scale ETL pipelines.
- Strong hands-on experience with AWS, particularly Amazon S3.
- Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
- Strong SQL skills and a solid understanding of distributed data processing concepts.
- Experience working with batch and/or streaming data pipelines.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with Databricks and the broader Databricks data platform.
- Familiarity with streaming technologies such as Apache Kafka.
- Experience working on large-scale data platforms handling high-volume data workloads.
- Exposure to additional AWS data services and cloud-native data architectures.









