solution engineer at GenZtechpro · Remote only · 2 - 5 years · ₹1L - ₹4L / yr · Bootstrapped · Remote only · Posted 23 Sep 2024

· Have Knowledge of the UC &/or CC platforms in the market (Chat, Meetings, Video, Phone, Marketplace/API)
· Having voice and Network knowledge, SaaS experience is nice to have
· Have solid business acumen and executive presence, able to position UC/CC Communication platform end-to-end

About GenZtechpro
About
GenZTechPro is an emerging IT recruitment startup company founded in 2024. Our journey began in the midst of industry layoffs, which inspired us to create a platform dedicated to helping Indian tech talent solve problems for upcoming startups and mid to large-scale companies. We are experts in hiring and providing end-to-end recruitment services for startups, SaaS, B2B, B2C, D2C, and MNCs. Our constant endeavour and commitment are to provide the best talent available in the industry to our clients. Vision "To be the leading global platform that empowers and connects the next generation of tech talent, driving innovation and shaping the future of technology." Mission "At GenZTechPro, our mission is to bridge the gap between emerging tech talent and industry leaders by providing unparalleled opportunities for learning, growth, and professional development. We strive to create a vibrant community where young innovators can collaborate, share knowledge, and turn their ideas into impactful solutions."
Candid answers by the company
IT service and Consulting
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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.
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.
role: data engineer
Python pyspark, SQL, data engineer
5+yrs
Bangalore/Hyderabad
immediate to 15days.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and PySpark.
- Work extensively with Databricks and Delta Lake, including Delta tables, MERGE operations, schema evolution, Time Travel, and data optimization.
- Develop, schedule, and monitor Apache Airflow DAGs for workflow orchestration and dependency management.
- Work with Kubernetes for containerized application deployment, orchestration, monitoring, and troubleshooting.
- Develop reusable and optimized Python code following software engineering best practices.
- Optimize Spark jobs for performance, scalability, and cost efficiency.
- Implement data quality checks, error handling, logging, and monitoring mechanisms.
- Use Git for version control, branching, pull requests, code reviews, and collaborative development.
- Troubleshoot pipeline failures, investigate data issues, and implement reliable solutions.
- Collaborate with cross-functional teams to understand business requirements and deliver efficient data solutions.
Required Technical Skills
- Python: Strong programming skills, including data manipulation, exception handling, modular programming, and debugging.
- PySpark: Hands-on experience with Spark DataFrames, Spark SQL, joins, transformations, partitioning, and performance tuning.
- Databricks: Strong understanding of Databricks architecture, notebooks, workflows, compute management, and job execution.
- Delta Lake: Experience with Delta tables, ACID transactions, MERGE/UPSERT, schema enforcement, schema evolution, VACUUM, and Time Travel.
- Apache Airflow: Experience developing DAGs, managing task dependencies, configuring retries, scheduling workflows, and troubleshooting failures.
- Kubernetes: Practical knowledge of pods, deployments, services, ConfigMaps, Secrets, resource management, and troubleshooting containerized workloads.
- Git: Proficiency in branching strategies, pull requests, merging, and resolving conflicts.
- SQL: Strong SQL skills, including complex joins, CTEs, window functions, and query optimization.
Good to Have
- Experience with Docker and containerization best practices.
- Experience with Databricks Unity Catalog and data governance.
- Knowledge of CI/CD pipelines and automated deployments.
- Experience deploying and managing Airflow workloads on Kubernetes.
- Familiarity with Kubernetes monitoring, autoscaling, and resource optimization.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Understanding of data lakehouse architecture and data modeling.
- Experience with batch and incremental data processing.
- Familiarity with data quality frameworks and automated testing.
Preferred Candidate Profile
- Strong analytical and problem-solving skills.
- Ability to independently design, develop, deploy, and troubleshoot data pipelines.
- Good understanding of distributed data processing and container orchestration.
- Experience working in an Agile development environment.
- Strong communication and collaboration skills.
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.
🚨 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
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.








