Data engineer - Bangalore Location at QAgile Services · Bengaluru (Bangalore) · 3 - 8 years · ₹17L - ₹25L / yr · Profitable · Posted 12 Aug 2025

Employment type- Contract basis
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using PySpark and distributed computing frameworks.
- Implement ETL processes and integrate data from structured and unstructured sources into cloud data warehouses.
- Work across Azure or AWS cloud ecosystems to deploy and manage big data workflows.
- Optimize performance of SQL queries and develop stored procedures for data transformation and analytics.
- Collaborate with Data Scientists, Analysts, and Business teams to ensure reliable data availability and quality.
- Maintain documentation and implement best practices for data architecture, governance, and security.
⚙️ Required Skills
- Programming: Proficient in PySpark, Python, and SQL, MongoDB
- Cloud Platforms: Hands-on experience with Azure Data Factory, Databricks, or AWS Glue/Redshift.
- Data Engineering Tools: Familiarity with Apache Spark, Kafka, Airflow, or similar tools.
- Data Warehousing: Strong knowledge of designing and working with data warehouses like Snowflake, BigQuery, Synapse, or Redshift.
- Data Modeling: Experience in dimensional modeling, star/snowflake schema, and data lake architecture.
- CI/CD & Version Control: Exposure to Git, Terraform, or other DevOps tools is a plus.
🧰 Preferred Qualifications
- Bachelor's or Master's in Computer Science, Engineering, or related field.
- Certifications in Azure/AWS are highly desirable.
- Knowledge of business intelligence tools (Power BI, Tableau) is a bonus.

About QAgile Services
About
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At Qagile Services, we are dedicated to empowering businesses through cutting-edge IT solutions and unparalleled staffing services. Our mission is to bridge the gap between technology and talent, ensuring that your organization has the resources it needs to thrive in a rapidly evolving digital landscape.
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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
Job Summary
We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.
Technical Skills
- Strong hands-on experience in Python and PySpark development.
- Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
- Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
- Experience with Power BI Data Modeling and Semantic Layer development.
- Proficiency in DAX (Data Analysis Expressions).
- Experience designing and managing Semantic Models in Power BI.
- Strong SQL skills and experience working with large datasets.
- Knowledge of data warehousing concepts and best practices.
Preferred Skills
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Exposure to modern data platforms like Databricks.
- Understanding of data governance and data quality frameworks.
We are hiring a Databricks Data Engineer to build scalable data pipelines on the lakehouse.
Responsibilities
- Build batch and streaming pipelines in Databricks with PySpark
- Model data in Delta Lake
- Optimise Spark jobs for cost and performance
- Set up data quality checks and monitoring
Requirements
- 2+ years of data engineering with Databricks
- Strong PySpark and Spark SQL skills
- Cloud experience on Azure, AWS or GCP
About the Role
We are looking for a Senior Data Engineer with strong hands-on expertise in Databricks, Python, PySpark, and SQL to build scalable, high-performance data engineering solutions. You’ll architect and develop large scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems. Databricks is the core enterprise data and processing platform for this role. You will also use Apache Airflow for workflow orchestration and dbt for ELT transformations, and will contribute to designing reliable, secure, and governed data platforms that enable analytics, reporting, and AI-driven use cases.
Key Responsibilities
- Design and implement large-scale data pipelines using Python/PySpark, Databricks, and Microsoft Fabric.
- Develop and optimize data processing workloads in Databricks using PySpark and Spark SQL, with a strong focus on scalability, reliability, performance, and maintainability.
- Develop and maintain dbt models including layered architecture, incremental models, snapshots, macros, testing, and documentation.
- Design, develop, and maintain Apache Airflow DAGs for orchestrating reliable, scalable, and observable data pipelines.
- Design and implement data quality, observability, and governance frameworks, including automated testing, monitoring, lineage, access control, and data privacy standards.
- Partner with analytics, product, and business stakeholders to turn requirements into trustworthy datasets, and raise the engineering bar through design discussions, code reviews, and mentoring junior engineers.
Required Skills
- Strong expertise in Python for developing scalable, modular, and production-ready data engineering applications.
- Strong expertise in PySpark, including DataFrame API, Spark SQL, Structured Streaming, partitioning strategies, joins, caching, handling data skew, and Spark performance optimization.
- Strong hands-on experience with Databricks for data ingestion, transformation, processing, and optimization, including Delta Lake, Unity Catalog, Databricks Workflows, notebooks, jobs, and Databricks-native data engineering capabilities.
- Strong experience in Databricks/Spark performance tuning, including query and job optimization, partitioning, file sizing, caching, join optimization, handling data skew, and efficient use of compute resources.
- Hands-on experience with Delta Lake, including transactional data processing, schema management, incremental data processing, and reliable batch and streaming data pipelines.
- Hands-on experience in developing dbt projects using layered architecture, incremental models, snapshots, macros/Jinja, testing, documentation, and deployment best practices.
- Expertise in advanced SQL and data modelling — dimensional modeling, slowly changing dimensions, schema evolution, and query optimization.
- Hands-on experience in developing and managing Apache Airflow DAGs, scheduling workflows, dependency management, retries, backfills, and operational monitoring.
- Hands-on experience with at least one major cloud platform (AWS, Azure or GCP).
- Strong problem-solving skills and the ability to work independently with business and analytics stakeholders.
Nice to Have
- Hands-on exposure to Microsoft Fabric for data integration and analytics.
- Experience using AI coding assistants (e.g. Claude Code, GitHub Copilot) as part of a development workflow.
- Familiarity with modern DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and containerization (Docker/Kubernetes).
- Domain expertise in financial services.
Responsibilities and JD
Job Description: We are looking for a Senior Developer with strong expertise in PySpark, Databricks, and Snowflake to build scalable data engineering solutions and enterprise data platforms.
Key Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
- Develop batch and real-time data processing solutions for structured and semi-structured data.
- Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
- Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
- Develop scalable data models, data marts, and data warehouse solutions.
- Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
- Implement data quality, validation, governance, and security controls.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
- Manage source control and CI/CD deployments using Git and Azure DevOps.
- Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
- Mentor junior team members and participate in code reviews and technical design discussions.
Required Skills: PySpark, Databricks, Snowflake, Python, SQL.
Experience: 5+ years of Data Engineering experience with strong hands-on expertise in PySpark, Databricks, and Snowflake.
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
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Job Title : Senior Data Engineer – Databricks
Experience : 14 to 20 Years
Location : HSR Layout, Bangalore
Work Mode : Hybrid – 3 Days WFO
Shift : 11:30 AM – 07:30 PM IST
Positions : 2
Notice Period : Immediate Joiners Only
Interview : 1 Technical Round + 2 Client Rounds
Role Overview :
We are looking for a Senior Data Engineer to build and lead enterprise-scale data platforms for a Switzerland-based commodity client.
The role requires a strong hands-on Data Engineering professional with expertise in Databricks, PySpark, Python, SQL, and AWS, along with technical leadership and stakeholder management experience.
Must-Have Skills :
- 14 to 20 years of Data Engineering experience
- Databricks & Apache Spark / PySpark
- Python & SQL
- AWS Cloud
- Lakehouse Architecture
- ETL / ELT & Distributed Data Processing
- Batch & Streaming Pipelines
- Data Pipeline Optimization & Data Modeling
- CDC & Incremental Processing
- Git, CI/CD & Testing
- Data Quality, Monitoring & Observability
- Technical Leadership & Stakeholder Management
Key Responsibilities :
- Design and build scalable data pipelines using Databricks, PySpark, Python, SQL, and AWS.
- Own data products from design through production.
- Develop batch / streaming pipelines and reusable ETL / ELT frameworks.
- Optimize pipelines for performance, scalability, reliability, and cost.
- Design scalable data architectures and data models.
- Implement data quality, monitoring, lineage, and CI/CD practices.
- Lead technical discussions and mentor engineering teams.
- Collaborate with business stakeholders, architects, product owners, and engineering teams.
- Remain hands-on while providing technical leadership.
Ideal Candidate :
A 14 to 20 years experienced, hands-on Data Engineering leader with strong Databricks + PySpark + AWS expertise, excellent communication, stakeholder management, and experience delivering enterprise-scale data platforms.
🔴 Super Urgent : Only Bangalore-based immediate joiners.
Senior Data Engineer – PySpark & Oracle
Experience: 7+ Years
Location: Bangalore
Notice Period: Immediate to 10 Days
Key Skills:
- Strong expertise in Data Modeling, Data Design & Modernization
- Primary skills: PySpark, Oracle SQL/PLSQL
- Secondary skills: Python, ETL & Data Pipelines
- Experience with Kafka and Hadoop
- Exposure to AWS / Azure / GCP
- Good knowledge of Git and JIRA
Roles & Responsibilities:
- Design, develop, and modernize scalable data models and data architecture.
- Develop and optimize data processing solutions using PySpark and Oracle SQL/PLSQL.
- Build and maintain robust ETL workflows and data pipelines.
- Work with Kafka, Hadoop, and cloud platforms for data processing and integration.
- Perform data transformation, optimization, and performance tuning.
- Collaborate with technical teams on data design, development, testing, and deployment.
🚨 WE ARE HIRING – SENIOR DATA ENGINEER | BANGALORE 🚨
Looking for experienced Senior Data Engineers with strong expertise in PySpark, Oracle SQL/PLSQL, and Data Modeling!
🔹 Role: Senior Data Engineer
🔹 Experience: 7+ Years
🔹 Location: Bangalore
🔹 CTC: Up to 26 LPA
🔹 Notice Period: Immediate to 10 Days Preferred
💻 Mandatory Skills
✅ PySpark
✅ Oracle SQL / PL/SQL
✅ Data Modeling & Design / Modernization
✅ Python
✅ ETL
✅ Data Pipelines
⚙️ Good to Have / Ecosystem Skills
✅ Kafka
✅ Hadoop
✅ AWS / Azure / GCP
✅ Git
✅ JIRA
📌 Key Responsibilities
• Develop and maintain scalable data pipelines using PySpark
• Work extensively with Oracle SQL/PLSQL for data processing and transformation
• Design and implement data models and data architecture
• Work on data design and modernization initiatives
• Develop and optimize ETL processes and data pipelines
• Handle large volumes of data using PySpark and Python
• Work with technologies such as Kafka, Hadoop, and Cloud platforms
• Collaborate with cross-functional teams to deliver scalable data solutions
• Use Git and JIRA for version control and project tracking
📩 Interested candidates can share their updated CV along with:
Total Experience:
Relevant PySpark Experience:
Relevant Oracle SQL/PLSQL Experience:
Data Modeling Experience:
Current Location:
Notice Period:
Current CTC:
Expected CTC:
#Hiring #DataEngineer #SeniorDataEngineer #PySpark #Oracle #PLSQL #DataModeling #Python #ETL #DataPipelines #Kafka #Hadoop #AWS #Azure #GCP #BangaloreJobs #ITJobs #TechJobs #ImmediateJoiners






