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

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

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

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.

Strong Data Engineer (AWS) Profile

2

Mandatory (Experience 1) – Must have minimum 6+ years of experience in Data Engineering, with strong experience designing, developing, and maintaining scalable data pipelines and ETL processes.

3

Mandatory (Experience 2) – Must have 3+ years of hands-on experience with AWS data engineering services, particularly S3, AWS Glue, EMR, Lambda, and Redshift.

4

Mandatory (Experience 3) – Must have strong programming experience in Python, Java, or Scala, with hands-on development of data processing and pipeline solutions.

5

Mandatory (Experience 4) – Must have strong expertise in SQL, data warehousing, and database technologies, including experience with both SQL and NoSQL databases.

6

Mandatory (Experience 5) – Must have hands-on experience working with Big Data technologies and distributed data processing, including designing and optimizing large-scale data pipelines.

7

Mandatory (Experience 6) – Must have experience with data pipeline troubleshooting, monitoring, data quality, governance, and security best practices.

8

Mandatory (Education) – B.Tech / B.E./ M.Tech

Position: Backup Data ETL Developer

Experience: 6–9 Years

Location:Mumbai

Employment Type: Full-time

Job Description:

We are looking for a Backup Data ETL Developer with 6–9 years of experience in designing, developing, and supporting data extraction, transformation, and loading (ETL) processes.

The candidate should have strong hands-on experience with Hadoop, Spark, Informatica, and Snowflake, along with expertise in large-scale data processing and data integration technologies.

Key Skills:

Hadoop

Spark

Informatica

Snowflake

ETL Development

Data Integration

Data Transformation

Large-Scale Data Processing

ETL Workflows and Data Pipelines

Troubleshooting and Problem-Solving

Strong analytical and collaboration skills

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 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.

1st virtual , 2nd round F2F

Python pyspark, SQL, data engineer

5+yrs

Bang/hyderabad

immediate to 15days.