Data Engineer

Experience: 6+ years overall Data Engineering experience.

Must-have — candidates should have hands-on experience in ALL of these:

1. GCP (Google Cloud Platform) – strong hands-on experience
2. Python – data engineering/ETL development
3. SQL – advanced SQL, query optimization, data transformation
4. BigQuery – strong hands-on experience with development, optimization and data warehousing
5. Data Engineering / ETL – building and maintaining data pipelines
6. GCP data services – preferably Cloud Storage, Dataflow, Pub/Sub, Composer/Airflow, etc.
7. Data warehousing / dimensional modeling

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

Role 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

Location: Hyderabad / Chennai

Experience: 5+ years

Employment type: Full-time, permanent

Work Hours: General Shift

website: www.amazech.com

Qualifications: 

• B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Data Science, or related disciplines.
• Strong academic background with relevant industry experience in Data Engineering and Data Warehousing.

Key Responsibilities:

·       Design, develop, and maintain scalable data warehouse solutions using Snowflake.

·       Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.

·       Develop and support ETL processes using Talend to ensure reliable and efficient data movement.

·       Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.

·       Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.

·       Debug and troubleshoot Python-based data processing scripts and automation workflows.

·       Implement best practices for data quality, testing, deployment, and code reviews.

·       Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.

·       Monitor, optimize, and maintain data warehouse performance and operational stability.

·       Create and maintain technical documentation, data models, and process workflows.

Required Skills and Experience: 

·       Strong hands-on expertise in Snowflake Data Warehouse.

·       Advanced SQL skills with experience handling large-scale datasets.

·       Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.

·       Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.

·       Experience developing and maintaining ETL solutions using Talend.

·       Proficiency in Python for scripting, debugging, automation, and data processing.

·       Experience integrating UI, API, and Data Warehouse workflows.

·       Strong problem-solving and analytical skills.

·       Experience with testing, code reviews, and deployment best practices.

·       Excellent communication and stakeholder management skills.

Experience: 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.

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

Job 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.

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

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

Senior Data Engineer – Ab Initio | GCP | Spark | Agentic AI

Location: Bangalore

Experience: 5+ Years

Role: Senior Data Engineer

Work Mode: Bangalore

Job Summary

We are looking for an experienced Senior Data Engineer with strong expertise in Ab Initio, GCP, Apache Spark, and Agentic AI. The ideal candidate will have hands-on experience designing and developing scalable data engineering solutions, building data pipelines, and working with modern cloud and AI technologies.

The candidate should be comfortable working across traditional enterprise data platforms and emerging Generative AI / Agentic AI solutions.

Key Responsibilities

• Design, develop, and maintain scalable and high-performance data pipelines using Ab Initio, Spark, and GCP services.
• Develop and optimize complex ETL/ELT workflows using Ab Initio.
• Build and maintain data processing solutions using Apache Spark / PySpark.
• Develop cloud-based data solutions on Google Cloud Platform (GCP).
• Work with GCP data services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, or equivalent services.
• Perform data integration, transformation, cleansing, and validation.
• Optimize data pipelines for performance, scalability, reliability, and cost.
• Collaborate with data architects,
•