Data Engineer

at PhotonMatters

Data Engineer

Data Engineer at PhotonMatters · Remote only · 4 - 13 years · ₹8L - ₹20L / yr · Bootstrapped · Remote only · Posted 16 Mar 2026

Data Engineer

at PhotonMatters

Posted by Human Resource

4 - 13 yrs

₹8L - ₹20L / yr

Remote only

Skills

Python

ETL

Spark

Amazon Web Services (AWS)

ELT

PySpark

Apache Kafka

Job Title: Data Engineer

Experience: 4–14 Years

Work Mode: Remote

Employment Type: Full-Time

Position Overview:

We are looking for highly experienced Senior Data Engineers to design, architect, and lead scalable, cloud-based data platforms on AWS. The role involves building enterprise-grade data pipelines, modernizing legacy systems, and developing high-performance scoring engines and analytics solutions and collaborate closely with architecture, analytics, risk, and business teams to deliver secure, reliable, and scalable data solutions.

Key Responsibilities:

· Design and build scalable data pipelines for financial and customer data

· Build and optimize scoring engines (credit, risk, fraud, customer scoring)

· Design, develop, and optimize complex ETL/ELT pipelines (batch & real-time)

· Ensure data quality, governance, reliability, and compliance standards

· Optimize large-scale data processing using SQL, Spark/PySpark, and cloud technologies

· Lead cloud data architecture, cost optimization, and performance tuning initiatives

· Collaborate with Data Science, Analytics, and Product teams to deliver business-ready datasets

· Mentor junior engineers and establish best practices for data engineering

Key Requirements:

· Strong programming skills in Python and advanced SQL

· Experience building scalable scoring or rule-based decision engines

· Hands-on experience with Big Data technologies (Spark/PySpark/Kafka)

· Strong expertise in designing ETL/ELT pipelines and data modeling

· Experience with cloud platforms (AWS/Azure) and modern data architectures

· Solid understanding of data warehousing, data lakes, and performance tuning

· Knowledge of CI/CD, version control (Git), and production support best practices

Job Title: Data Engineer

Experience: 4–14 Years

Work Mode: Remote

Employment Type: Full-Time

Position Overview:

We are looking for highly experienced Senior Data Engineers to design, architect, and lead scalable, cloud-based data platforms on AWS. The role involves building enterprise-grade data pipelines, modernizing legacy systems, and developing high-performance scoring engines and analytics solutions and collaborate closely with architecture, analytics, risk, and business teams to deliver secure, reliable, and scalable data solutions.

Key Responsibilities:

· Design and build scalable data pipelines for financial and customer data

· Build and optimize scoring engines (credit, risk, fraud, customer scoring)

· Design, develop, and optimize complex ETL/ELT pipelines (batch & real-time)

· Ensure data quality, governance, reliability, and compliance standards

· Optimize large-scale data processing using SQL, Spark/PySpark, and cloud technologies

· Lead cloud data architecture, cost optimization, and performance tuning initiatives

· Collaborate with Data Science, Analytics, and Product teams to deliver business-ready datasets

· Mentor junior engineers and establish best practices for data engineering

Key Requirements:

· Strong programming skills in Python and advanced SQL

· Experience building scalable scoring or rule-based decision engines

· Hands-on experience with Big Data technologies (Spark/PySpark/Kafka)

· Strong expertise in designing ETL/ELT pipelines and data modeling

· Experience with cloud platforms (AWS/Azure) and modern data architectures

· Solid understanding of data warehousing, data lakes, and performance tuning

· Knowledge of CI/CD, version control (Git), and production support best practices

Read more

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About PhotonMatters

Founded :

2022

Type :

Products & Services

Size :

20-100

Stage :

Bootstrapped

About

N/A

Company social profiles

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Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
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Job Summary:

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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.

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Lead the end-to-end design, development, and delivery of software systems, data pipelines, and components.

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Troubleshoot, debug, and resolve complex technical issues.

Drive continuous improvement in software and data development processes, tools, and methodologies.

Mentor and guide engineers through code reviews, technical discussions, and training.

Ensure timely delivery of projects while maintaining high engineering standards.

Continuously explore opportunities to enhance data quality and reliability.

Apply strong programming and problem-solving skills to develop scalable solutions.

Demonstrate passion for testing strategy, problem-solving, and continuous learning.

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Experience with RDBMS and OLAP databases such as MySQL and Snowflake.

Familiarity with Agile methodologies.

Obsession for service observability, instrumentation, monitoring, and alerting.

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About the Role

Wissen Technology is looking for experienced Python + AI / Data Engineering professionals to join our technology team in Bangalore. The ideal candidate will have strong hands-on experience in Python, Artificial Intelligence, Generative AI, PySpark, Snowflake, and data pipeline development.

The candidate should be capable of designing and developing scalable data and AI solutions, building robust ETL/ELT pipelines, working with large datasets, and integrating AI/ML capabilities into enterprise applications.

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Design, develop, and maintain scalable data pipelines using Python and PySpark.
Develop robust ETL/ELT pipelines for processing large volumes of structured and unstructured data.
Build and optimize data processing solutions using Apache Spark / PySpark.
Develop data ingestion and transformation pipelines into Snowflake.
Design and implement scalable Snowflake data models, tables, views, and SQL transformations.
Work with batch and, where applicable, real-time data processing pipelines.
Build and integrate AI and Generative AI solutions using Python.
Develop LLM-based applications, RAG solutions, AI agents, and AI-powered services.
Integrate AI models with enterprise data platforms and data pipelines.
Develop REST APIs and microservices using FastAPI, Flask, or Django.
Perform data cleansing, transformation, validation, and quality checks.
Optimize PySpark jobs, SQL queries, Snowflake workloads, and data pipelines for performance and scalability.
Implement data pipeline monitoring, logging, error handling, and alerting.
Work with cloud platforms such as AWS, Azure, or GCP.
Collaborate with Data Scientists, Data Engineers, Software Engineers, Architects, and business stakeholders.
Participate in technical design, architecture, code reviews, and production support.
Mentor junior engineers and contribute to engineering best practices.

Preferred Qualifications

Bachelor's or master's degree in computer science, Engineering, Data Science, Artificial Intelligence, or a related field.
Experience working on enterprise-scale AI and data engineering projects.
Experience combining Python + PySpark + Snowflake + AI/GenAI in production environments.
Experience with Databricks is an advantage.
Experience with AI Agents / Agentic AI and tool/function calling.
Knowledge of distributed systems and cloud-native architecture.
Experience leading technical initiatives or mentoring engineering teams.

Read more

Building enterprise data, cloud, and AI solutions.

Senior Data Engineer

Building enterprise data, cloud, and AI solutions.

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Upto ₹40L / yr (Varies

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SQL

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Amazon Web Services (AWS)

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You'll be at the forefront of designing and implementing robust data platform solutions that power advanced analytics, AI, and machine learning. Working with modern cloud technologies, you'll build scalable data foundations that enable clients to make smarter, data-driven decisions.

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Build scalable data pipelines using Snowflake, AWS, GCP, and Databricks.
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Develop reliable data foundations for MLOps, governance, and data lineage.
Integrate data from multiple sources into modern data platforms.
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Ensure data platforms are secure, scalable, and high-performing.

What We're Looking For

5+ years of hands-on experience with Snowflake.
Strong proficiency in SQL and Python.
Experience with AWS, Azure, or GCP.
Knowledge of cloud storage services such as S3, ADLS, or GCS.
Strong understanding of Dimensional Modeling and Data Vault.
Experience with Scala or Java is a plus.

Tech Stack

Data Warehouse: Snowflake
Programming: SQL, Python, Scala (Good to Have), Java (Good to Have)
Cloud: AWS, Azure, GCP
Storage: S3, ADLS, GCS
AI/ML: Snowpark ML, MLOps

Perks & Benefits

Public Speaking & Communication Program
Mentoring Program with Senior Support Leads
360° Progress Reviews
Weekly Learning Sessions & Guilds
Paid Certifications
Hackathons & Innovation Days
Recognition & Rewards Programs
Team Socials & Annual Offsites
Employee Assistance Program (24/7 Wellbeing Support)

The Data People Shaping Tomorrow

Our client helps organizations unlock the power of data through modern cloud, analytics, and AI solutions. We believe in creating an environment where talented technologists can learn, innovate, and make a real impact while building cutting-edge data platforms for global clients. If you're passionate about data engineering and want to work with the latest technologies in AI, cloud, and analytics, we'd love to hear from you.

About the Role

You'll be at the forefront of designing and implementing robust data platform solutions that power advanced analytics, AI, and machine learning. Working with modern cloud technologies, you'll build scalable data foundations that enable clients to make smarter, data-driven decisions.

Key Responsibilities

Build scalable data pipelines using Snowflake, AWS, GCP, and Databricks.
Design and optimize data models for AI and machine learning workloads.
Develop reliable data foundations for MLOps, governance, and data lineage.
Integrate data from multiple sources into modern data platforms.
Leverage Snowpark ML and Snowflake's native AI capabilities.
Ensure data platforms are secure, scalable, and high-performing.

What We're Looking For

5+ years of hands-on experience with Snowflake.
Strong proficiency in SQL and Python.
Experience with AWS, Azure, or GCP.
Knowledge of cloud storage services such as S3, ADLS, or GCS.
Strong understanding of Dimensional Modeling and Data Vault.
Experience with Scala or Java is a plus.

Tech Stack

Data Warehouse: Snowflake
Programming: SQL, Python, Scala (Good to Have), Java (Good to Have)
Cloud: AWS, Azure, GCP
Storage: S3, ADLS, GCS
AI/ML: Snowpark ML, MLOps

Perks & Benefits

Public Speaking & Communication Program
Mentoring Program with Senior Support Leads
360° Progress Reviews
Weekly Learning Sessions & Guilds
Paid Certifications
Hackathons & Innovation Days
Recognition & Rewards Programs
Team Socials & Annual Offsites
Employee Assistance Program (24/7 Wellbeing Support)

The Data People Shaping Tomorrow

Our client helps organizations unlock the power of data through modern cloud, analytics, and AI solutions. We believe in creating an environment where talented technologists can learn, innovate, and make a real impact while building cutting-edge data platforms for global clients. If you're passionate about data engineering and want to work with the latest technologies in AI, cloud, and analytics, we'd love to hear from you.

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Data Engineer

Dharani S

Posted by Dharani S

Bengaluru (Bangalore)

5 - 9 yrs

₹3L - ₹20L / yr

Python

DevOps

PySpark

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

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

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Senior Data Engineer – Databricks

Akshay Patil

Posted by Akshay Patil

Bengaluru (Bangalore)

14 - 25 yrs

₹50L - ₹70L / yr

Data engineering

databricks

Apache Spark

PySpark

Python

+19 more

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.

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.

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Data Engineer_Virtusa

Resume TGS

Posted by Resume TGS

The recruiter has not been active on this job recently. You may apply but please expect a delayed response.

Hyderabad

7 - 9 yrs

₹12L - ₹24L / yr

ELT

Google BigQuery

Python

Snow flake schema

SQL

+2 more

Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.
Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).
Work with cloud platforms GCP, Azure to manage data infrastructure.
GCP as mandatory skills
Collaborate with analytics and product teams to understand data needs and deliver solutions.
Ensure data quality, reliability, security, and compliance across all data systems.
Mentor junior data engineers and contribute to best practices and code reviews.
Monitor and troubleshoot data pipeline performance and resolve data-related issues.
Automate data validation, monitoring, and alerting processes.
8+ years of experience in data engineering or software engineering with a data focus.
Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
Strong understanding of data modeling, data lakes, and ETL/ELT design.
Hands-on experience with orchestration tools like Airflow, dbt, or similar.
Solid experience with cloud data platforms (AWS/GCP/Azure).
Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).
Experience working in a DevOps or DataOps environment.
Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).
Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).
Experience supporting machine learning workflows and data science initiatives.

Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.
Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).
Work with cloud platforms GCP, Azure to manage data infrastructure.
GCP as mandatory skills
Collaborate with analytics and product teams to understand data needs and deliver solutions.
Ensure data quality, reliability, security, and compliance across all data systems.
Mentor junior data engineers and contribute to best practices and code reviews.
Monitor and troubleshoot data pipeline performance and resolve data-related issues.
Automate data validation, monitoring, and alerting processes.
8+ years of experience in data engineering or software engineering with a data focus.
Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
Strong understanding of data modeling, data lakes, and ETL/ELT design.
Hands-on experience with orchestration tools like Airflow, dbt, or similar.
Solid experience with cloud data platforms (AWS/GCP/Azure).
Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).
Experience working in a DevOps or DataOps environment.
Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).
Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).
Experience supporting machine learning workflows and data science initiatives.

Read more

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