Data Platform Engineer (SDE 2 / SDE 3) at NeoGenCode Technologies Pvt Ltd · Remote, Pune · 3 - 8 years · ₹14L - ₹30L / yr · Raised funding · Remote friendly · Posted 28 Jul 2026

Job Title : Data Platform Engineer (SDE 2 / SDE 3)
Experience : 3 to 8 Years (SDE2 : 3 to 5 Years | SDE3 : 5.5 to 8 Years)
Location : Remote (Contract) → Pune (Post Conversion)
Employment Type : Contract-to-Hire (3 Months)
Mandatory Skills :
Java / Python / Go, SQL, Data Engineering, ETL / ELT, Apache Airflow, Apache Spark / Flink, Kafka, AWS/GCP/Azure, Distributed Systems, API Development, Docker, Kubernetes, CI/CD, System Design
Role Overview :
We are looking for a Data Platform Engineer with strong backend engineering expertise to build scalable, high-performance data platforms and distributed systems. The ideal candidate should have hands-on experience in developing production-grade backend applications along with designing and maintaining modern data pipelines.
Key Responsibilities :
- Build and maintain scalable ETL/ELT and data processing pipelines.
- Develop backend services and APIs using Java (preferred), Python, or Go.
- Design batch and real-time data pipelines using Spark, Flink, Kafka, and Airflow.
- Optimize SQL queries, data models, and distributed data systems.
- Work with cloud platforms (AWS, GCP, or Azure) and container technologies (Docker, Kubernetes).
- Implement CI/CD, monitoring, logging, and performance optimization.
- Collaborate with product and engineering teams on scalable system design and architecture.
Required Qualifications :
- SDE 2 : 3 to 5 years of Backend + Data Engineering experience.
- SDE 3 : 5.5 to 8 years of Backend + Data Engineering experience.
- Strong coding skills in Java (preferred), Python, or Go.
- Excellent SQL and data modeling knowledge.
- Hands-on experience with Airflow, Apache Spark / Apache Flink, or similar technologies.
- Experience building scalable backend services and APIs.
- Good understanding of distributed systems, system design. and scalable architecture.
- Experience with cloud platforms (AWS, Azure, or GCP).
- Hands-on experience with Docker and Kubernetes.
- Strong understanding of CI/CD pipelines.
- Excellent problem-solving and debugging skills.
Good to Have :
- Experience with Snowflake, BigQuery, or Redshift.
- Understanding of Kafka, Kinesis, or Pub/Sub
- Performance optimization of large-scale distributed systems
- FinTech or high-scale distributed systems experience.
- Knowledge of data governance, security, and compliance.
Preferred Candidate Profile :
- Strong Backend + Data Engineering experience
- Experience building scalable production systems
- Strong ownership mindset
- Good system design knowledge
- Experience processing millions of events using Kafka/Spark
- Built APIs supporting data infrastructure
- Production engineering experience
Interview Process :
- Take-home Coding Assignment (48 Hours)
- Leadership & Strategy Round (1 Hour)
- Technical Depth – Data Engineering & Performance (1 Hour)
- Culture & Values Fit (30 Minutes)

About NeoGenCode Technologies Pvt Ltd
About
Welcome to Neogencode Technologies, an IT services and consulting firm that provides innovative solutions to help businesses achieve their goals. Our team of experienced professionals is committed to providing tailored services to meet the specific needs of each client. Our comprehensive range of services includes software development, web design and development, mobile app development, cloud computing, cybersecurity, digital marketing, and skilled resource acquisition. We specialize in helping our clients find the right skilled resources to meet their unique business needs. At Neogencode Technologies, we prioritize communication and collaboration with our clients, striving to understand their unique challenges and provide customized solutions that exceed their expectations. We value long-term partnerships with our clients and are committed to delivering exceptional service at every stage of the engagement. Whether you are a small business looking to improve your processes or a large enterprise seeking to stay ahead of the competition, Neogencode Technologies has the expertise and experience to help you succeed. Contact us today to learn more about how we can support your business growth and provide skilled resources to meet your business needs.
Candid answers by the company
IT & Engineering Talent Staffing
- Provides full-time and contract-based hiring, delivering handpicked, pre‑screened developers across tech stacks—ranging from web, mobile, AI/ML, Web3/blockchain.
- Maintains a bench o vetted candidates, offering fast delivery of interview-ready profiles—often within 24 hours.
- Offers payroll management, handling compliance, tax, attendance, and documentation for both contractors and full-time employees.
2. End-to-End Project Delivery
- Delivers full-stack development solutions: web, mobile, cloud, AI/ML, Blockchain/Web3.
- Manages entire project lifecycle—requirements gathering, design (UI/UX), development, deployment, and ongoing support .
3. Additional Offerings
- Expands into cybersecurity consulting, digital marketing, and cloud platform services (like AWS, GCP, Azure) .
- Provides strategic IT consulting to align technology solutions with business objectives
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We are looking for a Data Engineer with at least 1 year of hands-on experience building solutions on Snowflake. The candidate should be comfortable designing, building, and managing reliable data pipelines that move data from multiple sources into a central data platform.
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- Build and maintain data pipelines for ingesting, transforming, and loading data into Snowflake
- Design scalable data models, schemas, tables, and views in Snowflake
- Develop ETL/ELT workflows using SQL, Python, or data orchestration tools
- Integrate data from APIs, databases, files, and third-party platforms
- Monitor pipeline performance, failures, data quality, and freshness
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- Implement incremental loads, change data capture, and scheduled workflows
- Work with engineering and business teams to understand data requirements
- Maintain documentation for pipelines, datasets, and data transformations
Requirements
- 1+ year of hands-on experience working with Snowflake
- Strong SQL skills and experience writing complex queries
- Experience building and managing ETL or ELT data pipelines
- Knowledge of data warehousing concepts, dimensional modelling, and data quality
- Experience with Python or another scripting language
- Familiarity with orchestration tools such as Airflow, Dagster, Prefect, dbt, or similar
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- Ability to troubleshoot pipeline failures and performance issues
- Strong analytical, problem-solving, and communication skills
Good to Have
- Experience with dbt and Snowflake Tasks, Streams, Snowpipe, or Dynamic Tables
- Knowledge of AWS, Azure, or Google Cloud
- Experience with Kafka or other streaming platforms
- Familiarity with CI/CD, Git, monitoring, and data governance practices
- Experience integrating ERP, finance, or operational systems
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.
Data Engineer Short Hiring Post
🚨 Hiring: Data Engineer
🔹 Experience: 5–9 Years
🔹 Location: Bangalore / Hyderabad
🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling
🔹 Process: L1 Virtual → L2 F2F Karat Test
🔹 F2F: Bangalore / Hyderabad Location
🔹 Positions: Immediate requirement
⚠️ Note: Candidates must be available for F2F Karat immediately after L1.
#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners
4 - 10 years of experience in designing and buildingarchitecting highly resilient data platforms
∙Strong knowledge of data engineering, architecture and data modeling
∙Experience in platforms like Databricks and Snowflake
∙Experience on building applications on cloud (AWS or Azure or Google Cloud)
∙Strong analytical and problem-solving skills
∙Prior experience in developing data or computation intensive (e.g. grid based) backend applications is an
advantage
∙OOP design skills with an understanding or at least personal interest towards the concepts of Functional
Programming
∙Willingness to understand and enhance other people’s code, being able to work in an environment where
developers will oversee and work on wider components also dealing with older “legacy” code
∙Strong programming skills (Java/ Scala / Python) skills with the willingness to pick up the other language if not
already mastered at a sufficient level is important
∙Spring knowledge is an advantage, but in general willingness to learn, work with and even enhance in-house
developed frameworks is a must
∙Prior experience in working with Git, Bitbucket, Jenkins, working with PR-s, using JIRA, following the Scrum Agile
methodology is an advantage
∙Prior knowledge of financial products is an advantage
∙Bachelors or Masters in any relevant field of IT/Engineering area is an advantage
Job 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
Job Summary
We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.
Key Responsibilities
- Design, develop, and maintain ETL/ELT data pipelines.
- Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
- Develop automation scripts using Python for data processing and workflow optimization.
- Work with Linux environments for deployment, monitoring, and troubleshooting.
- Ensure data quality, integrity, and reliability across data platforms.
- Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
- Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
- Implement best practices for data security, governance, and documentation.
Required Skills
- Strong experience in Data Engineering concepts and ETL/ELT processes.
- Proficiency in SQL, including query optimization and database design.
- Strong programming skills in Python.
- Hands-on experience with Linux commands, shell scripting, and system administration basics.
- Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
- Familiarity with Git/version control.
- Strong analytical and problem-solving skills.
Preferred Skills
- Experience with cloud platforms (AWS, Azure, or GCP).
- Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
- Experience with data warehousing solutions and big data technologies.
- Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Relevant certifications in cloud or data engineering are an added advantage.
Key Responsibilities
Build and maintain data transformation pipelines using java Spark
Develop and optimize large-scale/CPU intensive data processing using Apache Spark
Orchestrate workflows using Airflow
Implement data quality checks, testing, and monitoring for pipeline. Good to have exposer into managing metadata, cataloguing, and lineage
Support schema evolution, backfills, and incremental processing
Ensure pipelines meet SLAs for freshness, reliability, and performance
Expertise/working knowledge in Spark and HBase(semantic layer, virtual datasets, Reflections)
Required Skills & Qualifications
Strong hands-on experience with Apache Spark
Experience with HBase/SQL or similar lakehouse query engines
Airflow
Understanding of data catalogs and lineage (e.g., OpenLineage, DataHub, Apache Polaris , openlineage)
Proficiency in Java
Experience with Git-based development and CI/CD
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. 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.
- 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.
Job Title: Data Engineer – PySpark | Oracle | GCP
Experience: 5–7 Years
Location: Hyderabad
Notice Period: Immediate Joiners Preferred
Job Summary
We are seeking an experienced Data Engineer with strong expertise in PySpark, Oracle, and Google Cloud Platform (GCP) to design, develop, and optimize scalable data pipelines. The ideal candidate should have hands-on experience in ETL development, data integration, and cloud-based data engineering solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL/data pipelines using PySpark.
- Extract, transform, and load data from Oracle databases into GCP environments.
- Build and optimize batch data processing workflows for high performance and reliability.
- Develop data engineering solutions using GCP services.
- Ensure data quality through validation, monitoring, and troubleshooting.
- Optimize SQL queries and ETL jobs for performance and scalability.
Required Skills
- 5–7 years of experience as a Data Engineer.
- Strong hands-on experience with PySpark.
- Solid experience with Oracle Database and advanced SQL.
- Hands-on experience with Google Cloud Platform (GCP).
- Strong understanding of ETL processes and data warehousing concepts.
Work Location: Hyderabad
Notice Period: Immediate Joiners Preferred






