Senior Data Engineer with AWS at dataeaze systems · Remote only · 5 - 8 years · ₹12L - ₹22L / yr · Profitable · Remote only · Posted 26 Oct 2023
POST - SENIOR DATA ENGINEER WITH AWS
Experience : 5 years
Must-have:
• Highly skilled in Python and PySpark
• Have expertise in writing Glue jobs ETL script, AWS
• Experience in working with Kafka
• Extensive SQL DB experience – Postgres
Good-to-have:
• Experience in working with data analytics and modelling
• Hands on Experience of PowerBI visualization tool
• Knowledge and hands-on on version control system - Git Common:
• Excellent communication and presentation skills (written and verbal) to all levels
of an organization
• Should be results oriented with ability to prioritize and drive multiple initiatives to
complete work you're doing on time
• Proven ability to influence a diverse geographically dispersed group of
individuals to facilitate, moderate, and influence productive design and implementation
discussions driving towards results
Shifts - Flexible ( might have to work as per US Shift timings for meetings ).
Employment Type - Any

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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.
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.
Data Engineer
Location: Bengaluru, India (Hybrid)
Employment Type: Full-time
Experience: 3-5 years
Role Overview
What We’re Looking For:
- Bachelor’s degree in Computer Science/Engineering or equivalent experience required.
- Experience designing and shipping cloud services products.
- Experience driving and managing technical and architectural dependencies on AWS Cloud.
- A firm understanding of system architecture, cloud computing, PaaS/SaaS design principles, S3, DynamoDB, RDS mandatory.
- Experience in building or maintaining ETL processes and tools, i.e., AWS Glue or any open-source tool.
- Proven system-level design contribution to a current “Live” (in production / under daily high load) multi-region SaaS or PaaS offering.
- Proven experience with S3, DynamoDB, SQL, and AWS RDS services.
- Proficiency in programming languages such as Python.
- Strong analytical and problem-solving skills.
Required Skills & Experience
- Experience with Python, SQL, and data visualization/exploration tools.
- Familiarity with the AWS ecosystem, specifically S3, DynamoDB, and RDS.
- Communication skills, especially for explaining technical concepts to nontechnical business leaders.
- Ability to work on a dynamic, research-oriented team that has concurrent projects.
- Experience in AWS cost optimization (Savings Plans, Reserved Instances, Spot Instances) and governance frameworks.
- Experience developing solutions using infrastructure orchestration tools (SSM, automation account, Ansible, etc.).
- Excellent leadership, stakeholder management, and communication skills.
What We Offer
- Work with some of the brightest minds in the emerging EV industry.
- Make a tangible impact in reducing carbon emissions and enabling sustainable energy.
- Freedom to suggest, implement, and innovate on systems, processes, and technologies.
- Daily ownership in a high-growth, challenging environment.
- Flexible work environment with hybrid schedules and virtualization options.
- Competitive pay and benefits including health coverage, innovative PTO program, and performance bonuses.
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.
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
Description
We are looking for Senior Data Engineers to join our Data Platform team and build scalable, high-performance data platforms that power data processing, analytics, and downstream applications.
The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Apache Spark and Python Scala.
You will be responsible for designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL and data processing pipelines for large-scale datasets.
- Build and optimize distributed data applications using Apache Spark and Python Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Design and manage data workflows using Apache Airflow.
- Build and operate data workloads on AWS, with strong usage of Amazon S3 for large-scale data storage.
- Work with large datasets to ensure data quality, consistency, reliability, and performance.
- Collaborate with engineering, product, analytics, and other platform teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, performance, and cost efficiency.
- Troubleshoot production issues, identify bottlenecks, and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering, Big Data Engineering, or a similar role.
- Strong hands-on experience with Apache Spark and Scala.
- Experience designing, building, and maintaining large-scale ETL pipelines.
- Strong hands-on experience with AWS, particularly Amazon S3.
- Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
- Strong SQL skills and a solid understanding of distributed data processing concepts.
- Experience working with batch and/or streaming data pipelines.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with Databricks and the broader Databricks data platform.
- Familiarity with streaming technologies such as Apache Kafka.
- Experience working on large-scale data platforms handling high-volume data workloads.
- Exposure to additional AWS data services and cloud-native data architectures.
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
Skills Referential (Required knowledge, skills and abilities)
Technical Skills:
Python
Pyspark
SQL
ETL Aws, Azure, gcp
Job 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
🚨 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






