BACKUP DATA ETL DEVELOPER

Dear Candidate,

Thanks for showing interest in the opportunity!!!

As discussed, we have an opening for ETL Developer – Hadoop & PySpark with Mphasis for the Bangalore location – Permanent.

Job Description:

We are looking for an experienced ETL Developer with strong expertise in ETL development, Hadoop, and PySpark. The candidate should have hands-on experience in data processing, building and maintaining ETL pipelines, data transformation, and handling large datasets using Big Data technologies.

Primary & Mandatory Skills:

• ETL Development
• Hadoop / HDFS
• PySpark / Apache Spark
• Data Extraction, Transformation & Loading
• SQL and Data Processing

Good to Have:

• Hive / Spark SQL
• Data Pipeline Development
• Big Data Processing
• Python Programming

Company: Mphasis

Role: ETL Developer – Hadoop & PySpark

Experience: As per requirement

Location: Bangalore

Employment Type: Permanent

Hiring: ETL Developer – Hadoop & PySpark

Location: Bangalore

Experience: 6–10 Years

Budget: 25–30 LPA

Work Mode: Weekdays

Job Description

We are looking for an experienced ETL Developer with strong expertise in Hadoop, PySpark, Python, and SQL to design, develop, and optimize data processing and transformation solutions. The ideal candidate should have hands-on experience working with big data technologies, building scalable ETL pipelines, and managing data for data warehousing and analytics.

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines for large-scale data processing.
• Develop data transformation workflows using PySpark and Python.
• Work with Hadoop and other big data technologies to process and manage large datasets.
• Write complex SQL queries for data extraction, transformation, validation, and analysis.
• Implement data cleansing, data quality checks, and data validation processes.
• Develop and optimize data integration workflows for data warehousing solutions.
• Troubleshoot ETL failures, performance issues, and data discrepancies.
• Optimize PySpark jobs and SQL queries for performance and scalability.
• Collaborate with data engineers, architects, analysts, and other stakeholders to deliver reliable data solutions.
• Ensure data accuracy, consistency, and adherence to established data governance standards.

Mandatory Skills

• Strong hands-on experience in ETL development.
• Good experience with Hadoop and big data technologies.
• Proficiency in PySpark and Python programming.
• Strong SQL skills, including complex queries and data manipulation.
• Experience in data processing, data transformation, and data integration.
• Understanding of data warehousing concepts and architecture.
• Experience in developing, debugging, and optimizing ETL pipelines.

Required Experience

• 6–10 years of relevant experience in ETL development and data engineering.
• Practical experience handling large datasets using Hadoop and PySpark.
• Strong analytical, problem-solving, and troubleshooting skills.
• Ability to work independently and collaborate effectively within a team.

Interested candidates can share their updated resumes along with current CTC, expected CTC, notice period, and total relevant experience.

Job Description

We are looking for an experienced ETL Developer with strong expertise in ETL development, Hadoop, PySpark, Python, and SQL. The candidate should have hands-on experience in developing data pipelines, processing and transforming large datasets, and working with data warehousing and big data technologies.

Key Responsibilities

• Design, develop, and maintain ETL processes and data pipelines.
• Work with Hadoop and PySpark to process and transform large volumes of data.
• Develop and optimize Python scripts for data processing and automation.
• Write complex SQL queries for data extraction, transformation, and validation.
• Perform data cleansing, integration, transformation, and validation.
• Work with data warehousing concepts and large-scale data processing systems.
• Optimize ETL workflows for performance, scalability, and reliability.
• Troubleshoot data pipeline failures and resolve data quality issues.
• Collaborate with data engineers, analysts, and other technical teams.
• Follow data governance, quality, and development best practices.

Required Skills

• Strong experience in ETL Development – Mandatory
• Hands-on experience with Hadoop – Mandatory
• Strong experience in PySpark – Mandatory
• Good programming skills in Python – Mandatory
• Strong knowledge of SQL – Mandatory
• Experience in Data Processing and Transformation – Mandatory
• Knowledge of Data Warehousing – Mandatory
• Experience with Big Data Technologies – Mandatory

Opportunity Details

Role: ETL Developer – Hadoop & PySpark

Experience: 6–10 Years

Location: Bangalore

Mandatory Skills

ETL Development | Hadoop | PySpark | Python | SQL | Data Processing & Transformation | Data Warehousing | Big Data Technologies

We are looking for Data engineer with strong expertise in Data warehousing to join our team.

Key skills : ab initio, ssis , Informatica, Hadoop and Teradata

Data Engineer Hiring Post

🚨 Hiring: Data Engineer | PySpark + Python + SQL

We are looking for experienced Data Engineers to join our team!

🔹 Experience: 5 to 9 Years

🔹 Locations: Bangalore / Hyderabad

🔹 Interview Process:

• 1st Round – Virtual

• 2nd Round – Face-to-Face (Karat Test)

🔑 Key Skills:

✅ PySpark

✅ SQL

✅ Python

✅ ETL

📩 Interested candidates can share their updated resume.

#Hiring #DataEngineer #PySpark #Python #SQL #ETL #BangaloreJobs #HyderabadJobs #TechHiring #ImmediateHiring

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

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.

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 :

1. Take-home Coding Assignment (48 Hours)
2. Leadership & Strategy Round (1 Hour)
3. Technical Depth – Data Engineering & Performance (1 Hour)
4. Culture & Values Fit (30 Minutes)

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.

Location: Hyderabad / Chennai

Experience: 5+ years

Employment type: Full-time, permanent

Work Hours: General Shift

website: www.amazech.com

Qualifications: 

• B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Data Science, or related disciplines.
• Strong academic background with relevant industry experience in Data Engineering and Data Warehousing.

Key Responsibilities:

·       Design, develop, and maintain scalable data warehouse solutions using Snowflake.

·       Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.

·       Develop and support ETL processes using Talend to ensure reliable and efficient data movement.

·       Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.

·       Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.

·       Debug and troubleshoot Python-based data processing scripts and automation workflows.

·       Implement best practices for data quality, testing, deployment, and code reviews.

·       Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.

·       Monitor, optimize, and maintain data warehouse performance and operational stability.

·       Create and maintain technical documentation, data models, and process workflows.

Required Skills and Experience: 

·       Strong hands-on expertise in Snowflake Data Warehouse.

·       Advanced SQL skills with experience handling large-scale datasets.

·       Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.

·       Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.

·       Experience developing and maintaining ETL solutions using Talend.

·       Proficiency in Python for scripting, debugging, automation, and data processing.

·       Experience integrating UI, API, and Data Warehouse workflows.

·       Strong problem-solving and analytical skills.

·       Experience with testing, code reviews, and deployment best practices.

·       Excellent communication and stakeholder management skills.