Data Engineer

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

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

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

Shift: Second Shift (2:00 PM – 10:00 PM)

Joining: Immediate

About the Role

We are looking for an experienced Data Integration Developer with strong hands-on expertise in SQL, Python, ETL development, Snowflake, and AWS data services.

The ideal candidate should have extensive experience in designing, developing, and maintaining data integration solutions, building data warehouse architectures, and implementing scalable ETL pipelines. Strong SQL development and performance optimization skills are essential for this role.

This is a remote position; however, candidates must be available to visit our Mumbai or Bangalore location for three days during the onboarding process.

Key Responsibilities

SQL Development & Performance Optimization

• Develop complex SQL queries, stored procedures, and data transformation logic.
• Optimize SQL queries for performance, scalability, and efficiency.
• Perform advanced data analysis, validation, and reconciliation.
• Troubleshoot complex SQL and data-related issues.

ETL Development & Data Integration

• Design, develop, and maintain ETL pipelines and data integration workflows.
• Work with SQL and Python for data extraction, transformation, and loading.
• Ensure data accuracy, consistency, and integrity across systems.
• Identify and resolve data pipeline failures and integration issues.

Data Warehousing & Data Modeling

• Design and maintain data warehouse architectures.
• Develop data warehouse schemas based on business requirements.
• Work on dimensional data modeling, including Facts and Dimensions.
• Implement Slowly Changing Dimensions (SCD).
• Support data analysis and business information reconciliation.

Snowflake & AWS

• Develop and manage data solutions using Snowflake.
• Work with AWS services, particularly Amazon S3.
• Manage AWS connections and data access configurations.
• Build and maintain cloud-based data integration solutions.

Python & Apache Airflow

• Develop data processing and automation solutions using Python.
• Build, schedule, and monitor workflows using Apache Airflow.
• Troubleshoot workflow failures and improve pipeline reliability.

Agile & Development Lifecycle

• Participate in Agile development processes, sprint planning, and team discussions.
• Contribute throughout all stages of the software development lifecycle.
• Collaborate with cross-functional teams to understand business and technical requirements.
• Perform root cause analysis and implement appropriate corrective actions.

Required Skills

• Advanced SQL – Strong hands-on expertise is mandatory.
• Python Development
• ETL Development and Data Integration
• Snowflake
• Apache Airflow
• AWS Services, particularly Amazon S3
• AWS Connection Management
• Data Warehouse Architecture
• Data Modeling (Facts & Dimensions)
• Slowly Changing Dimensions (SCD)
• SQL Query Optimization and Performance Tuning
• Data Analysis and Reconciliation
• Troubleshooting and Root Cause Analysis
• Agile Development Methodologies
• Strong understanding of the Software Development Life Cycle (SDLC)

Experience & Qualifications

• 8–10 years of overall experience in Data Engineering / Data Integration / ETL Development.
• Strong professional experience in advanced SQL and Python.
• Hands-on experience with Snowflake, Apache Airflow, and AWS.
• Proven experience designing and developing data warehouse solutions.
• Experience working across the complete product development lifecycle.
• Ability to independently troubleshoot complex technical challenges.

Additional Requirements

• Immediate joiners preferred.
• Must be comfortable working in the second shift (2:00 PM – 10:00 PM).
• Position is remote, with a mandatory three-day onboarding visit to Mumbai or Bangalore.
• Strong communication, analytical, and problem-solving skills.
• Ability to work independently and collaboratively in an Agile environment.

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

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

Data Engineer

Experience - 5+ years

6-7 LPA

Remote

Duration: 1 month contract (We can take as a tentative, It can be extended)

Scope: Subscriber Activation, Churn, FTE and future reporting requirements, with BigQuery as the centralized data warehouse and Power BI as the proposed reporting layer.

Key Skills:

Strong hands-on experience with GCP & BigQuery

Data warehouse architecture, design and implementation

Data ingestion/integration across multiple source systems

ETL/ELT and data pipeline development

Data modelling for reporting and analytics

Experience integrating BigQuery with Power BI or similar reporting tools

Job Title : Data / AI / GenAI – Engineering & Analytics

Experience : 4+ Years

Location : Noida / Gurugram / Ahmedabad

Employment Type : Full-time | On-site at client location

Working Days : 5 days per week

Working Hours : Standard business hours

Position Overview : We are seeking professionals to deliver modern data engineering, business intelligence, cloud analytics and AI-powered applications, according to their specialization.

Mandatory Skills :

Python, SQL, ETL/ELT, Data Engineering, Power BI, Azure Data Factory, Databricks, PySpark, Data Modeling, GenAI/LLMs, RAG, Vector Databases, AI Agents (as per role specialization).

Key Roles / Specializations :

1. Power BI Developers : Dashboards, DAX, Power Query, reporting and data modeling
2. Azure Data Engineers : Azure Data Factory, Data Lake, Azure SQL and cloud pipelines
3. Databricks Engineers : Apache Spark, PySpark, Delta Lake and scalable processing
4. Data Engineers : ETL/ELT, SQL, Python, data warehousing and quality
5. GenAI / RAG Engineers : LLMs, prompts, embeddings, vector databases and retrieval pipelines
6. Agentic AI Engineers : AI agents, tool calling, orchestration and multi-agent workflows

Key Responsibilities :

• Design, develop and maintain data pipelines, analytics solutions or AI applications.
• Build and optimize data integration, transformation and processing workflows.
• Develop dashboards and analytical models for business decision-making.
• Use cloud data platforms and modern engineering frameworks.
• Develop and evaluate LLM applications, RAG solutions or AI agents as applicable.
• Ensure data quality, security, performance and reliability.
• Collaborate with engineering teams and stakeholders on testing, deployment and documentation.

Required Skills & Qualifications :

• Bachelor’s degree in Computer Science, IT, Data Science, Engineering or related discipline.
• 4–5 years of relevant experience in data, analytics, AI or software engineering.
• Hands-on expertise in at least one listed specialization; not all technologies are required.
• Relevant Python, SQL, DAX or other technical skills depending on the position.
• Understanding of cloud platforms, APIs, integration and software practices.

Preferred Qualifications :

• Azure, Databricks or Microsoft Fabric experience.
• For GenAI roles : Azure OpenAI, OpenAI APIs, LangChain, LlamaIndex or LangGraph.
• For relevant roles : vector databases, CI/CD, Docker, MLOps or LLMOps.

Note : Candidates are expected to have expertise in their relevant specialization, not in every listed technology or role.

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 – Contract Opportunity

We are looking for an experienced Data Engineer with 5+ years of experience to work on subscriber activation, churn, FTE, and future reporting requirements.

Key Responsibilities:

• Work on data requirements related to Subscriber Activation, Churn, FTE, and future reporting.
• Work with BigQuery as the centralized data warehouse.
• Develop and maintain data ingestion and integration pipelines across multiple source systems.
• Design and implement ETL/ELT processes.
• Develop data models for reporting and analytics.
• Integrate BigQuery with Power BI or similar reporting tools.

Required Skills:

• Strong hands-on experience with GCP & BigQuery
• Data warehouse architecture, design, and implementation
• Data ingestion/integration across multiple source systems
• ETL/ELT and data pipeline development
• Data modelling for reporting and analytics
• Experience integrating BigQuery with Power BI or similar reporting tools

Contract: 1 month initially, with potential extension

Compensation: ₹6–7 LPA

Work Mode: Remote

Important

Since this is only a 1-month contract, mention “Potential extension” rather than saying it will definitely be extended.