Data Engineer at RedSeer Consulting · Bengaluru (Bangalore) · 0 - 2 years · ₹10L - ₹15L / yr · Posted 11 Jul 2022
BRIEF DESCRIPTION:
At-least 1 year of Python, Spark, SQL, data engineering experience
Primary Skillset: PySpark, Scala/Python/Spark, Azure Synapse, S3, RedShift/Snowflake
Relevant Experience: Legacy ETL job Migration to AWS Glue / Python & Spark combination
ROLE SCOPE:
Reverse engineer the existing/legacy ETL jobs
Create the workflow diagrams and review the logic diagrams with Tech Leads
Write equivalent logic in Python & Spark
Unit test the Glue jobs and certify the data loads before passing to system testing
Follow the best practices, enable appropriate audit & control mechanism
Analytically skillful, identify the root causes quickly and efficiently debug issues
Take ownership of the deliverables and support the deployments
REQUIREMENTS:
Create data pipelines for data integration into Cloud stacks eg. Azure Synapse
Code data processing jobs in Azure Synapse Analytics, Python, and Spark
Experience in dealing with structured, semi-structured, and unstructured data in batch and real-time environments.
Should be able to process .json, .parquet and .avro files
PREFERRED BACKGROUND:
Tier1/2 candidates from IIT/NIT/IIITs
However, relevant experience, learning attitude takes precedence

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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.
Location: Bangalore Experience: 5 to 7 years Employment type: Full-time, permanent Work Hours: General Shift (10.00 AM to 7.00 PM) website: www.amazech.com Qualifications: Minimum B.E./B.Tech, or higher in Computer Science, Information Technology, Data Engineering, or a related field, with a good academic background. Key Responsibilities: • Design, develop, and maintain end-to-end data pipelines. • Build and optimize ETL/ELT processes for large-scale data processing. • Implement Azure-based data solutions ensuring scalability and performance. • Collaborate with stakeholders to understand business data requirements. • Perform performance tuning and optimization across data platforms. • Support production environments, conduct root cause analysis, and resolve data-related issues. • Maintain comprehensive technical documentation and structured knowledge transfer documents. • Work effectively within Agile/Scrum frameworks and contribute to sprint planning and delivery. • Ensure secure and compliant data handling using Azure best practices. Required Skills & Experience • End-to-end ETL/ELT pipeline development, integration, and performance optimization • Azure Synapse, Azure Logic Apps, Azure SQL, and Azure Databricks, with a strong focus on performance tuning • Microsoft Azure services, including Storage Accounts, Key Vault, and Cognitive Services • Advanced proficiency in Python development and modern productivity tools such as GitHub Copilot and Cursor • Strong documentation discipline, including technical design documentation, and structured knowledge transfer documents • Experience operating within Agile/Scrum frameworks, including production support, root cause analysis, and effective stakeholder collaboration
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 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 Description – Azure Data Engineer
Role: Azure Data Engineer
Experience: 9+ Years
Location: Bangalore / Hyderabad
Notice Period: Immediate to 15 Days
Interview Process: 1st Round – Virtual | 2nd Round – F2F
Mandatory Skills
- Python
- PySpark
- SQL
- Azure Data Engineering
Job Description
We are looking for an experienced Azure Data Engineer with 9+ years of experience and strong hands-on expertise in Python, PySpark, SQL, and Azure Data Engineering.
Key Responsibilities
- Develop and maintain scalable data engineering solutions using Azure.
- Build and optimize data processing pipelines using PySpark and Python.
- Write complex SQL queries for data extraction and transformation.
- Work with Azure data services and cloud-based data platforms.
- Perform data processing, transformation, and integration.
- Troubleshoot data pipeline and production issues.
- Collaborate with technical and business teams to deliver data solutions.
Preferred: Immediate to 15 Days joiners.
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.
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:
- Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
- Develop batch and real-time data processing solutions for structured and semi-structured data.
- Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
- Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
- Develop scalable data models, data marts, and data warehouse solutions.
- Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
- Implement data quality, validation, governance, and security controls.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
- Manage source control and CI/CD deployments using Git and Azure DevOps.
- Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
- 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.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
9+yrs
Bangalore/Hyderabad
immediate to 15days.
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
Urgent Hiring – Senior Data Engineer
We are hiring for a Senior Data Engineer for a reputed product-based company in Pune.
Location: Pune – Magarpatta / Baner
Experience: 7–10 Years
Work Mode: 5 Days WFO
Notice Period: Immediate to 30 Days preferred
What We're Looking For
- 7+ years of hands-on experience in Data Engineering
- 5+ years of experience in Python
- 4+ years of experience in Snowflake
- 5+ years of experience in SQL
- 5+ years of experience with ADF / Fivetran / Matillion or equivalent Data Integration tools
- Hands-on experience with AWS / Azure
- Experience with Airflow or equivalent orchestration tools
- Strong experience in ETL/ELT and Data Pipelines
- Experience with APIs, JSON, XML and Webhooks
- Knowledge of CI/CD, Git and automated testing
- Exposure to dbt or similar transformation tools
- Experience in data pipeline monitoring, troubleshooting and performance optimization
Key Responsibilities
- Design, develop and maintain scalable ETL/ELT data pipelines
- Build batch, real-time and on-demand data processing workflows
- Integrate data from cloud and on-premise sources
- Ensure data quality, reliability, performance and SLA adherence
- Work closely with Data Scientists, Analysts, DevOps and Business teams
- Implement data engineering best practices, CI/CD and automated testing
- Troubleshoot pipeline issues and perform root cause analysis
- Optimize data pipelines and SQL queries for performance and cost efficiency
Why Join?
- Opportunity to work with a reputed product-based organization
- Work on modern data engineering and cloud technologies
- Exposure to large-scale data platforms and business-critical data solutions
- Collaborative and technically strong environment
Interested candidates can share their updated CV for immediate consideration.







