Data Engineer (PySpark+SQL) at Fragma Data Systems · Remote, Bengaluru (Bangalore) · 3.5 - 8 years · ₹5L - ₹18L / yr · Profitable · Remote friendly · Posted 3 Sep 2021

- Building and operationalizing large scale enterprise data solutions and applications using one or more of AZURE data and analytics services in combination with custom solutions - Azure Synapse/Azure SQL DWH, Azure Data Lake, Azure Blob Storage, Spark, HDInsights, Databricks, CosmosDB, EventHub/IOTHub.
- Experience in migrating on-premise data warehouses to data platforms on AZURE cloud.
- Designing and implementing data engineering, ingestion, and transformation functions
-
Azure Synapse or Azure SQL data warehouse
-
Spark on Azure is available in HD insights and data bricks
- Experience with Azure Analysis Services
- Experience in Power BI
- Experience with third-party solutions like Attunity/Stream sets, Informatica
- Experience with PreSales activities (Responding to RFPs, Executing Quick POCs)
- Capacity Planning and Performance Tuning on Azure Stack and Spark.

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Job Description – Data Engineer
Role: Data Engineer
Experience: 9+ Years
Location: Bangalore / Hyderabad
Notice Period: Immediate to 15 Days
Interview Process: 1st Round – Virtual | 2nd Round – F2F
Mandatory Skills
- Python
- PySpark
- SQL
- Azure Data Engineering
Job Description
We are looking for an experienced Azure Data Engineer with 9+ years of experience and strong hands-on expertise in Python, PySpark, SQL, and Azure Data Engineering.
Key Responsibilities
- Develop and maintain scalable data engineering solutions using Azure.
- Build and optimize data processing pipelines using PySpark and Python.
- Write complex SQL queries for data extraction and transformation.
- Work with Azure data services and cloud-based data platforms.
- Perform data processing, transformation, and integration.
- Troubleshoot data pipeline and production issues.
- Collaborate with technical and business teams to deliver data solutions.
Preferred: Immediate to 15 Days joiners.
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.
Job Description:
We are seeking a skilled Senior Data Engineer with expertise in Databricks to join our dynamic data team. The ideal candidate will design, build, and maintain scalable data pipelines and architectures to support our organization's data-driven initiatives and leverage Databricks to process large-scale datasets, optimize data workflows, enable advanced analytics and machine learning, and integrate Power BI for data visualization and reporting.
Key Responsibilities
· 5-8 years of professional work experience in a relevant field
· Proficient in Microsoft Fabric platform, Azure Databricks, ADF, Delta Lake, SQL Data Warehouse, Unity Catalog.
· Good Experience on Microsoft Dynamics 365
· Experience/ prior knowledge on semi structure data and Structured Streaming, Azure synapse, data lake, data warehouse.
· Proficient in creating Azure Data Factory pipelines for ETL/ELT processing; copy activity, custom Azure development etc.
· Good knowledge of SQL and Python for data manipulation, transformation, and analysis
· Understand business requirements to set functional specifications for reporting applications
- Data Pipeline Development: Design, develop, and maintain robust, scalable data pipelines using Databricks, Apache Spark, and other cloud-based technologies.
- Data Integration: Ingest, transform, and integrate data from diverse sources, including APIs, databases, streaming platforms, and third-party systems, into Databricks for analytics and reporting.
- Power BI Integration: Develop and optimize data models and datasets in Databricks for use in Power BI, ensuring efficient data connections and high-quality visualizations.
- Performance Optimization: Optimize data workflows, API calls, and queries on Databricks and Power BI for performance, cost-efficiency, and scalability.
- Data Modeling: Build and maintain data models to support business requirements, ensuring data quality, consistency, and accessibility for analytics and reporting.
- Cloud Integration: Implement data solutions on cloud platforms (e.g., AWS, Azure, GCP) integrated with Databricks, Power BI, and API ecosystems.
- Security & Compliance: Implement data governance, security, and compliance best practices within Databricks, Power BI, and API environments.
- Technical Skills:
- Proficiency in Databricks, including Delta Lake, Spark SQL.
- Strong programming skills in Python, Scala, or Java.
- Experience with Apache Spark for big data processing.
- Knowledge of SQL for querying and transforming data.
- Proficiency in Power BI for creating data models, DAX queries, and interactive dashboards.
Preferred Qualifications
- Databricks certification (e.g., Databricks Certified Data Engineer Associate/Professional).
Experience with real-time data processing and streaming
Location: Bangalore Experience: 5 to 7 years Employment type: Full-time, permanent Work Hours: General Shift (10.00 AM to 7.00 PM) website: www.amazech.com Qualifications: Minimum B.E./B.Tech, or higher in Computer Science, Information Technology, Data Engineering, or a related field, with a good academic background. Key Responsibilities: • Design, develop, and maintain end-to-end data pipelines. • Build and optimize ETL/ELT processes for large-scale data processing. • Implement Azure-based data solutions ensuring scalability and performance. • Collaborate with stakeholders to understand business data requirements. • Perform performance tuning and optimization across data platforms. • Support production environments, conduct root cause analysis, and resolve data-related issues. • Maintain comprehensive technical documentation and structured knowledge transfer documents. • Work effectively within Agile/Scrum frameworks and contribute to sprint planning and delivery. • Ensure secure and compliant data handling using Azure best practices. Required Skills & Experience • End-to-end ETL/ELT pipeline development, integration, and performance optimization • Azure Synapse, Azure Logic Apps, Azure SQL, and Azure Databricks, with a strong focus on performance tuning • Microsoft Azure services, including Storage Accounts, Key Vault, and Cognitive Services • Advanced proficiency in Python development and modern productivity tools such as GitHub Copilot and Cursor • Strong documentation discipline, including technical design documentation, and structured knowledge transfer documents • Experience operating within Agile/Scrum frameworks, including production support, root cause analysis, and effective stakeholder collaboration
We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.
Qualifications and Skills:
- Minimum 5 years of experience as a Data Engineer
- Hands-on experience with Azure cloud-based data solutions
- Expertise in database design and management, including SQL databases such as SQL Server
- Proficient in ETL (Extract, Transform, Load) design for data integration and processing
- Strong knowledge of data modeling principles and techniques
- Ability to analyze and translate data into actionable insights, reports, and visualizations
- Proficiency in Power BI for reporting and data visualization
Desirable Skills:
- Experience with Power BI Report Builder / Reporting Services
- Knowledge of statistical analysis or Data Science
- Experience within the UK Insurance industry is a plus
- Python or R coding skills
Responsibilities:
- Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
- Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
- Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
- Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
- Implement different methods of streaming data and create reconciliations for datasets
- Build analytical models to support reporting and analytics
- Collaborate with an agile delivery team to work on the backlog of specified work
8-12 years experience on Data Engineering role working with Databricks & Azure Cloud technologies.
• Bachelor’s degree in computer science, Information Technology, or related field.
• Strong proficiency in PySpark, Python, SQL.
• Strong experience in data modeling, ETL/ELT pipeline development, and automation • Hands-on experience with performance tuning of data pipelines and workflow
• Proficient in working on Azure cloud components Azure Data Factory, Azure DataBricks, Azure Data Lake etc.
• Experience with data modeling, ETL processes, Delta Lake and data warehousing.
• Experience on Delta Live Tables, Autoloader & Unity Catalog.
Preferred - Knowledge of the insurance industry and its data requirements.
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Excellent communication and problem-solving skills to work effectively with diverse teams
• Excellent problem-solving skills and ability to work under tight deadlines.
Company: Wissen Technology
Position: Databricks Engineer
Experience: 6-10 Years
Location: Bengaluru/Mumbai
Employment Type: Full-time
About Wissen Technology
Wissen Technology is a global technology services company focused on delivering innovative software engineering, data, and technology solutions to leading enterprises. The company works with clients across industries to build scalable, high-performance technology platforms and solve complex business and technology challenges.
With a strong focus on engineering excellence, innovation, and collaboration, Wissen Technology brings together skilled technology professionals across areas such as software engineering, data engineering, cloud, analytics, and digital transformation.
At Wissen Technology, employees have the opportunity to work on challenging technology projects, collaborate with experienced engineering teams, and contribute to solutions that create measurable business impact.
Key Responsibilities
- Design, develop, and maintain scalable data processing applications using Python, PySpark, and Spark.
- Develop and optimize data pipelines and workflows on Databricks.
- Collaborate with data engineers, data scientists, business stakeholders, and other technical teams to understand requirements and deliver high-quality solutions.
- Ensure data integrity, quality, performance, and reliability across data processing pipelines.
- Write clean, maintainable, scalable, and efficient code following established coding standards and best practices.
- Perform data analysis and implement appropriate data validation and quality checks.
- Monitor, troubleshoot, and optimize performance issues across data workflows and pipelines.
- Work with relational databases and develop efficient SQL queries for data extraction and transformation.
- Participate in code reviews, testing, deployment, and continuous improvement of data engineering solutions.
- Use Git/version control and follow established software development and deployment practices.
Required Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
- Proven experience as a Databricks Developer, Data Engineer, or similar role.
- Strong hands-on expertise in Apache Spark and PySpark.
- Strong programming skills in Python; experience with Scala is an advantage.
- Strong proficiency in SQL and hands-on experience with relational databases.
- Practical experience developing and optimizing data pipelines and data processing applications.
- Familiarity with Git and version control systems.
- Strong understanding of data engineering concepts, data transformation, and data validation.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.
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.
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 :
- Power BI Developers : Dashboards, DAX, Power Query, reporting and data modeling
- Azure Data Engineers : Azure Data Factory, Data Lake, Azure SQL and cloud pipelines
- Databricks Engineers : Apache Spark, PySpark, Delta Lake and scalable processing
- Data Engineers : ETL/ELT, SQL, Python, data warehousing and quality
- GenAI / RAG Engineers : LLMs, prompts, embeddings, vector databases and retrieval pipelines
- 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.
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.











