GCP Data Engineer at Cymetrix Software · Remote only · 3 - 7 years · ₹8L - ₹20L / yr · Profitable · Remote only · Posted 13 Mar 2026
PythonMust have skills:
1. GCP - GCS, PubSub, Dataflow or DataProc, Bigquery, Airflow/Composer, Python(preferred)/Java
2. ETL on GCP Cloud - Build pipelines (Python/Java) + Scripting, Best Practices, Challenges
3. Knowledge of Batch and Streaming data ingestion, build End to Data pipelines on GCP
4. Knowledge of Databases (SQL, NoSQL), On-Premise and On-Cloud, SQL vs No SQL, Types of No-SQL DB (At least 2 databases)
5. Data Warehouse concepts - Beginner to Intermediate level
Role & Responsibilities:
● Work with business users and other stakeholders to understand business processes.
● Ability to design and implement Dimensional and Fact tables
● Identify and implement data transformation/cleansing requirements
● Develop a highly scalable, reliable, and high-performance data processing pipeline to extract, transform and load data
from various systems to the Enterprise Data Warehouse
● Develop conceptual, logical, and physical data models with associated metadata including data lineage and technical
data definitions
● Design, develop and maintain ETL workflows and mappings using the appropriate data load technique
● Provide research, high-level design, and estimates for data transformation and data integration from source
applications to end-user BI solutions.
● Provide production support of ETL processes to ensure timely completion and availability of data in the data
warehouse for reporting use.
● Analyze and resolve problems and provide technical assistance as necessary. Partner with the BI team to evaluate,
design, develop BI reports and dashboards according to functional specifications while maintaining data integrity and
data quality.
● Work collaboratively with key stakeholders to translate business information needs into well-defined data
requirements to implement the BI solutions.
● Leverage transactional information, data from ERP, CRM, HRIS applications to model, extract and transform into
reporting & analytics.
● Define and document the use of BI through user experience/use cases, prototypes, test, and deploy BI solutions.
● Develop and support data governance processes, analyze data to identify and articulate trends, patterns, outliers,
quality issues, and continuously validate reports, dashboards and suggest improvements.
● Train business end-users, IT analysts, and developers.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Cymetrix Software
About
Cymetrix is a global CRM and Data Analytics consulting company. It has expertise across industries such as manufacturing, retail, BFSI, NPS, Pharma, and Healthcare. It has successfully implemented CRM and related business process integrations for more than 50+ clients.
Catalyzing Tangible Growth: Our pivotal role involves facilitating and driving actual growth for clients. We're committed to becoming a catalyst for dynamic transformation within the business landscape.
Niche focus, limitless growth: Cymetrix specializes in CRM, Data, and AI-powered technologies, offering tailored solutions and profound insights. This focused approach paves the way for exponential growth opportunities for clients.
A Digital Transformation Partner: Cymetrix aims to deliver the necessary support, expertise, and solutions that drive businesses to innovate with unwavering assurance. Our commitment fosters a culture of continuous improvement and growth, ensuring your innovation journey is successful.
The Cymetrix Software team is under the leadership of agile, entrepreneurial, and veteran technology experts who are devoted to augmenting the value of the solutions they are delivering.
Our certified team of 150+ consultants excels in Salesforce products. We have experience in designing and developing products and IPs on the Salesforce platform enables us to design industry-specific, customized solutions, with intuitive user interfaces.
Candid answers by the company
Cymetrix is a global CRM and Data Analytics consulting company. It has expertise across industries such as manufacturing, retail, BFSI, NPS, Pharma, and Healthcare. It has successfully implemented CRM and related business process integrations for more than 50+ clients.
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Similar jobs (10)
Job Summary
We are seeking a highly skilled GCP Data Engineer with strong expertise in Google Cloud Platform (GCP), Python, ETL, and modern data engineering technologies. The ideal candidate should have hands-on experience designing and building scalable data pipelines using BigQuery, Dataflow, Pub/Sub, Airflow, and modern data lake technologies such as Apache Iceberg or Delta Lake.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines on Google Cloud Platform.
- Build and optimize data processing workflows using Python and Google Cloud Dataflow (Apache Beam).
- Develop and manage large-scale analytical data models in BigQuery.
- Implement event-driven data ingestion using Google Cloud Pub/Sub.
- Create, schedule, and monitor workflows using Apache Airflow and Autosys.
- Design and implement modern data lake architectures using Apache Iceberg or Delta Lake.
- Optimize query performance, storage, and compute costs in GCP.
- Ensure data quality, governance, security, and compliance across data platforms.
- Collaborate with Data Scientists, Analysts, and Application teams to deliver scalable data solutions.
- Troubleshoot production issues and continuously improve pipeline reliability and performance.
Mandatory Skills
- Strong hands-on experience with Google Cloud Platform (GCP).
- Proficiency in Python programming.
- Experience in designing and implementing ETL/ELT pipelines.
- Strong knowledge of BigQuery.
- Experience with Google Cloud Dataflow (Apache Beam).
- Experience with Google Cloud Pub/Sub.
- Hands-on experience with Apache Airflow.
- Experience in job scheduling using Autosys.
- Experience with modern table formats such as Apache Iceberg or Delta Lake.
- Strong SQL and data modeling skills.
Preferred Skills
- Experience with Cloud Storage, Dataproc, Cloud Composer, and Cloud Functions.
- Knowledge of CI/CD pipelines and DevOps practices.
- Experience with Docker and Kubernetes.
- Familiarity with Git and Agile/Scrum methodologies.
- Knowledge of data warehousing and dimensional modeling.
- Exposure to streaming and real-time data processing.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
- 4–8+ years of experience in Data Engineering with hands-on expertise in GCP technologies.
Required Experience
- Strong experience in developing enterprise-grade data pipelines using Python and GCP.
- Hands-on experience with BigQuery, Dataflow, Pub/Sub, and Airflow.
- Experience scheduling and monitoring batch workflows using Autosys.
- Experience implementing modern data lake architectures using Apache Iceberg or Delta Lake.
- Strong understanding of ETL best practices, performance tuning, and data optimization.
- Excellent analytical, troubleshooting, and problem-solving skills.
Mandatory Skills
- Google Cloud Platform (GCP)
- Python
- ETL
- BigQuery
- Autosys
- Apache Airflow
- Google Cloud Pub/Sub
- Google Cloud Dataflow (Apache Beam)
- Apache Iceberg / Delta Lake
- SQL & Data Modeling
PythonJob 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
PythonRole Overview
We are looking for a GCP Data Engineer with 10+ years of experience to design, develop, and optimize scalable cloud-based data solutions. The ideal candidate will have strong hands-on expertise in GCP, BigQuery, and advanced SQL, with experience building data pipelines and working with large-scale datasets.
Key Responsibilities
- Design and develop scalable data pipelines and ETL/ELT processes on GCP.
- Build, optimize, and maintain data solutions using Google BigQuery.
- Develop complex SQL queries for data transformation, aggregation, and analysis.
- Design efficient data models and optimize pipelines for performance, scalability, and cost.
- Integrate data from multiple sources and ensure data quality, reliability, and availability.
- Troubleshoot pipeline and data issues and drive continuous improvement.
- Collaborate with data architects, analysts, application teams, and business stakeholders.
- Follow best practices for cloud security, data governance, testing, and documentation.
Required Skills
- 8+ years of Data Engineering experience
- Strong hands-on experience with GCP, Django, and MongoDB
- Extensive experience with BigQuery
- Advanced SQL skills
- Strong understanding of ETL/ELT and data pipeline development
- Data modeling and data warehousing experience
- Experience handling large-scale datasets and performance optimization
- Strong problem-solving and communication skills
Good to Have
- GCP services such as Cloud Storage, Dataflow, Pub/Sub, Cloud Composer, or Cloud Functions
- Python or other data engineering languages
- Experience with data governance and security
- Agile development experience
We are hiring a GCP Data Engineer to build scalable data pipelines on Google Cloud.
Responsibilities
- Build batch and streaming pipelines with Dataflow and Pub/Sub
- Model and optimise data warehouses in BigQuery
- Run large-scale processing on Dataproc
- Orchestrate workflows with Cloud Composer
Requirements
- 2+ years of data engineering on Google Cloud
- Hands-on with BigQuery and Dataflow
- Strong data modelling and SQL optimisation skills
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
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
We are looking for a Data Engineer with at least 1 year of hands-on experience building solutions on Snowflake. The candidate should be comfortable designing, building, and managing reliable data pipelines that move data from multiple sources into a central data platform.
Responsibilities
- Build and maintain data pipelines for ingesting, transforming, and loading data into Snowflake
- Design scalable data models, schemas, tables, and views in Snowflake
- Develop ETL/ELT workflows using SQL, Python, or data orchestration tools
- Integrate data from APIs, databases, files, and third-party platforms
- Monitor pipeline performance, failures, data quality, and freshness
- Optimize Snowflake queries, warehouses, storage, and compute usage
- Implement incremental loads, change data capture, and scheduled workflows
- Work with engineering and business teams to understand data requirements
- Maintain documentation for pipelines, datasets, and data transformations
Requirements
- 1+ year of hands-on experience working with Snowflake
- Strong SQL skills and experience writing complex queries
- Experience building and managing ETL or ELT data pipelines
- Knowledge of data warehousing concepts, dimensional modelling, and data quality
- Experience with Python or another scripting language
- Familiarity with orchestration tools such as Airflow, Dagster, Prefect, dbt, or similar
- Understanding of APIs, relational databases, file formats, and cloud storage
- Ability to troubleshoot pipeline failures and performance issues
- Strong analytical, problem-solving, and communication skills
Good to Have
- Experience with dbt and Snowflake Tasks, Streams, Snowpipe, or Dynamic Tables
- Knowledge of AWS, Azure, or Google Cloud
- Experience with Kafka or other streaming platforms
- Familiarity with CI/CD, Git, monitoring, and data governance practices
- Experience integrating ERP, finance, or operational systems
PythonExperience: 6+ years overall Data Engineering experience.
Must-have — candidates should have hands-on experience in ALL of these:
- GCP (Google Cloud Platform) – strong hands-on experience
- Python – data engineering/ETL development
- SQL – advanced SQL, query optimization, data transformation
- BigQuery – strong hands-on experience with development, optimization and data warehousing
- Data Engineering / ETL – building and maintaining data pipelines
- GCP data services – preferably Cloud Storage, Dataflow, Pub/Sub, Composer/Airflow, etc.
- Data warehousing / dimensional modeling
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
PythonJob Summary
We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.
Key Responsibilities
- Design, develop, and maintain ETL/ELT data pipelines.
- Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
- Develop automation scripts using Python for data processing and workflow optimization.
- Work with Linux environments for deployment, monitoring, and troubleshooting.
- Ensure data quality, integrity, and reliability across data platforms.
- Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
- Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
- Implement best practices for data security, governance, and documentation.
Required Skills
- Strong experience in Data Engineering concepts and ETL/ELT processes.
- Proficiency in SQL, including query optimization and database design.
- Strong programming skills in Python.
- Hands-on experience with Linux commands, shell scripting, and system administration basics.
- Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
- Familiarity with Git/version control.
- Strong analytical and problem-solving skills.
Preferred Skills
- Experience with cloud platforms (AWS, Azure, or GCP).
- Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
- Experience with data warehousing solutions and big data technologies.
- Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Relevant certifications in cloud or data engineering are an added advantage.
PythonExperience: 5+ Years
Employment Type: Full-Time
Role Overview
We are looking for an experienced GCP Data Engineer with 5+ years of experience in data engineering and strong hands-on expertise in Google BigQuery, Google Cloud Storage (GCS), Airflow/Cloud Composer, Python, and Vertex AI. The candidate should be capable of designing, developing, and maintaining scalable data pipelines and cloud-based data solutions on Google Cloud Platform.
Key Skills – Mandatory
- BigQuery – Strong hands-on experience in data warehousing, SQL, optimization, and performance tuning.
- Google Cloud Storage (GCS) – Experience with data storage, file management, and integration with data pipelines.
- Airflow / Cloud Composer – Experience in developing, scheduling, monitoring, and managing data workflows.
- Python – Strong programming skills for data engineering, ETL/ELT development, automation, and pipeline implementation.
- Vertex AI – Experience working with ML/AI workflows, model integration, or data pipelines supporting AI/ML solutions.
Good to Have / Added Advantage
- Dataproc – Experience with distributed data processing and Spark-based workloads.
- Cloud Data Fusion – Experience in building and managing data integration pipelines.
- Cloud Run – Understanding of deploying and running containerized applications/services on GCP.
- Experience with ETL/ELT processes and data pipeline development.
- Knowledge of GCP data architecture and cloud-native services.
- Experience in data quality, validation, monitoring, and troubleshooting.
Responsibilities
- Design, develop, and maintain scalable GCP-based data pipelines.
- Build and optimize data solutions using BigQuery and Cloud Storage.
- Develop and manage workflows using Airflow / Cloud Composer.
- Write efficient and reusable Python code for data processing and automation.
- Support Vertex AI integrations and AI/ML data workflows.
- Monitor pipeline performance and troubleshoot data processing issues.
- Work with cross-functional teams to understand data requirements and deliver reliable solutions.
- Implement best practices for data security, quality, scalability, and performance.
You must have :
- 5+ years of overall experience in Data Engineering.
- Strong hands-on experience with BigQuery, GCS, Airflow/Cloud Composer, Python, and Vertex AI.
- Strong understanding of data engineering concepts, ETL/ELT, data pipelines, and cloud technologies.
- Dataproc, Data Fusion, and Cloud Run experience will be an added advantage.
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon