Platform Engineer at Mobile Programming LLC · Chennai · 4 - 7 years · ₹13L - ₹15L / yr · Profitable · Posted 12 Jun 2023
Title: Platform Engineer Location: Chennai Work Mode: Hybrid (Remote and Chennai Office) Experience: 4+ years Budget: 16 - 18 LPA
Responsibilities:
- Parse data using Python, create dashboards in Tableau.
- Utilize Jenkins for Airflow pipeline creation and CI/CD maintenance.
- Migrate Datastage jobs to Snowflake, optimize performance.
- Work with HDFS, Hive, Kafka, and basic Spark.
- Develop Python scripts for data parsing, quality checks, and visualization.
- Conduct unit testing and web application testing.
- Implement Apache Airflow and handle production migration.
- Apply data warehousing techniques for data cleansing and dimension modeling.
Requirements:
- 4+ years of experience as a Platform Engineer.
- Strong Python skills, knowledge of Tableau.
- Experience with Jenkins, Snowflake, HDFS, Hive, and Kafka.
- Proficient in Unix Shell Scripting and SQL.
- Familiarity with ETL tools like DataStage and DMExpress.
- Understanding of Apache Airflow.
- Strong problem-solving and communication skills.
Note: Only candidates willing to work in Chennai and available for immediate joining will be considered. Budget for this position is 16 - 18 LPA.

About Mobile Programming LLC
About
Mobile programming LLC is a US based MNC company. Our services are focused on Mobility Solutions, Custom App Development, Cloud Solutions, IoT, AR/VR, Blockchain, Artificial Intelligence & Machine Learning, Predictive Analytics & Big Data Solutions, and several other trending as well as emerging technologies.
You can find more details on - https://www.mobileprogramming.com/
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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
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.
4 - 10 years of experience in designing and buildingarchitecting highly resilient data platforms
∙Strong knowledge of data engineering, architecture and data modeling
∙Experience in platforms like Databricks and Snowflake
∙Experience on building applications on cloud (AWS or Azure or Google Cloud)
∙Strong analytical and problem-solving skills
∙Prior experience in developing data or computation intensive (e.g. grid based) backend applications is an
advantage
∙OOP design skills with an understanding or at least personal interest towards the concepts of Functional
Programming
∙Willingness to understand and enhance other people’s code, being able to work in an environment where
developers will oversee and work on wider components also dealing with older “legacy” code
∙Strong programming skills (Java/ Scala / Python) skills with the willingness to pick up the other language if not
already mastered at a sufficient level is important
∙Spring knowledge is an advantage, but in general willingness to learn, work with and even enhance in-house
developed frameworks is a must
∙Prior experience in working with Git, Bitbucket, Jenkins, working with PR-s, using JIRA, following the Scrum Agile
methodology is an advantage
∙Prior knowledge of financial products is an advantage
∙Bachelors or Masters in any relevant field of IT/Engineering area is an advantage
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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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.
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.
About Us
We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable.
Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.
We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life.
Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk.
Our Guiding Principles
These principles define how we work at Incubyte. They are non-negotiable.
Relentless Pursuit of Quality with Pragmatism
We build high-quality systems without losing sight of delivery.
Extreme Ownership
We take responsibility end-to-end for decisions, execution, and outcomes.
Proactive Collaboration
We collaborate closely, challenge each other, and solve problems together.
Active Pursuit of Mastery
We continuously improve our craft and raise our bar.
Invite, Give, and Act on Feedback
We seek, give, and act on feedback to get better every day.
Ensuring Client Success
We act as trusted partners and focus on real outcomes, not just output.
Job Description
This is a remote position.
Experience Level
2+ years of experience in SQL, Python, and Snowflake (or equivalent cloud data warehouse), Azure Cloud services.
Role Overview
If you're a Data Craftsperson who takes pride in clean, well-tested data solutions and believes in the principles of Extreme Programming, we'd love to meet you. At Incubyte, we're a DevOps organization where developers own the entire release cycle — you'll get hands-on experience across data engineering, analytics, cloud infrastructure, and direct client communication. This role sits primarily in data engineering (80%) with a meaningful analytics component (20%), supporting our client's data systems end-to-end.
What You'll Do
- Design, build, and maintain data pipelines and infrastructure using SQL and Python
- Work within Snowflake to build and optimize data models supporting business use cases
- Parse and process structured and semi-structured data (JSON, XML) from varied sources
- Diagnose issues across raw, intermediate, and summary tables
- Build SQL queries to support repeatable analytics use cases based on stakeholder requirements
- Investigate and resolve data quality issues, including time-sensitive or urgent ones
- Identify opportunities to consolidate models and maintain a single source of truth (SSOT)
Requirements
What We're Looking For
- 2+ years of experience with SQL and relational databases, with the ability to understand complex data relationships and transformations (required)
- 2+ years of experience with Python for data engineering tasks (required)
- Experience with Snowflake or an equivalent cloud data warehouse (required)
- Experience working with Snowflake Coco or any other AI tools(required)
- Experience parsing JSON and XML data (a plus)
- A strong eye for data quality and attention to detail
- Knowledge of Git (required)
- Knowledge of Azure cloud services such as Azure Data Factory, Azure Blob Storage, and Azure SQL Database (required)
- Knowledge of data infrastructure/modeling tools like DBT, Fivetran (a plus)
- Experience with BI tools like Power BI(a plus, not core to this role)
- Knowledge of Docker, Linux, Shell/Bash, and virtualization technologies (a plus)
- Knowledge of SSIS packages (a plus)
- Familiarity with CI/CD methodologies
Benefits
Life at Incubyte
We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered.
Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion.
Perks
- Dedicated learning & development budget.
- Sponsorship for conference talks.
- Comprehensive medical & term insurance.
- Employee-friendly leave policies.
- Home Office fund
- Medical Insurance
Job Title : Data Engineer – Databricks
Experience : 6+ Years
Location : Noida / Hyderabad / Chennai / Pune / Bengaluru (Hybrid)
Shift : IST (Normal Shift)
Job Summary :
We are seeking an experienced Data Engineer with strong expertise in Databricks, Snowflake, Python, and Spark to build and optimize scalable data pipelines and support AI/ML model deployments. The ideal candidate should have experience working with cloud-based data platforms and preferably possess exposure to the Healthcare domain.
Required Skills :
- Databricks (Preferred)
- Snowflake
- Python
- Apache Spark
- SQL
- Azure Cloud
- Kubernetes
- Apache Airflow
- GitHub & CI/CD Pipelines
- AI/ML Model Deployment
- Data Analytics
Preferred :
- Experience in the Healthcare domain.
- Strong understanding of scalable data engineering architectures and best practices.
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.

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.






