Sr Python Developer

1st virtual , 2nd round F2F -

Python pyspark, SQL, data engineer

5+yrs

Bang/hyderabad

immediate to 15days.

1st virtual , 2nd round F2F

Python pyspark, SQL, data engineer

5+yrs

Bang/hyderabad

immediate to 15days.

1st virtual , 2nd round F2F

Python pyspark, SQL, data engineer

5+yrs

9+yrs

Bangalore/Hyderabad

immediate to 15days.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Python, Hadoop, and Apache Spark.
• Develop efficient data processing and transformation workflows for large datasets.
• Write, optimize, and maintain complex SQL queries and PL/SQL procedures.
• Perform data extraction, transformation, and loading (ETL) from multiple data sources.
• Work with structured and unstructured data to support analytics and reporting requirements.
• Optimize data pipelines and queries for performance, scalability, and reliability.
• Ensure data quality, consistency, security, and integrity across data platforms.
• Collaborate with cross-functional teams to understand business requirements and deliver data engineering solutions.
• Use Git, automation, and CI/CD practices to support development and deployment.

Required Skills

• 4.5–10 years of experience in software development or data engineering.
• Strong proficiency in AWS
• Hands-on experience with Hadoop and Apache Spark.
• Good knowledge of SQL and PL/SQL, including query optimization and stored procedures.
• Experience in ETL development, data processing, and data pipeline design.
• Understanding of data warehousing concepts and distributed computing.
• Strong problem-solving, debugging, and performance-tuning skills.

role: data engineer

Python pyspark, SQL, data engineer

5+yrs

Bangalore/Hyderabad

immediate to 15days.

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.

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

Job Details:

• Role: Python Developer
• Location: Bangalore
• Experience: 7+ Years
• Required Skills:
• Python Development
• MySQL
• REST API Development
• Django Framework
• PySpark

INTERESTED CANDIDATE SEND YOUR RESUME IN MAIL OR WHATSAPP :

Email: revathi.r @vysystems. com

WhatsApp / Call: 6 3 8 5 0 7 6 1 4 2

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:

1. Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
2. Develop batch and real-time data processing solutions for structured and semi-structured data.
3. Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
4. Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
5. Develop scalable data models, data marts, and data warehouse solutions.
6. Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
7. Implement data quality, validation, governance, and security controls.
8. Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
9. Manage source control and CI/CD deployments using Git and Azure DevOps.
10. Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
11. 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.

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.