Data Engineer at Mango Sciences · Remote only · 5 - 7 years · ₹10L - ₹15L / yr · Raised funding · Remote only · Posted 29 May 2026

Job description:
Role Overview
We are seeking a Senior SQL Developer & ETL Engineer with 5+ years of experience for a 100% remote opportunity.
Please note: This is not a standard Big Data / Infra-heavy Data Engineering role. We are specifically looking for a SQL Specialist. Your core strength must lie in relational database development, schema design, and writing high-performance database logic. Python will be your primary tool for moving and orchestrating data, but SQL and database architecture are the heart of this role.
Key Responsibilities
- Database Architecture & Schema Design: Design, implement, and maintain robust relational database schemas, ensuring optimal data modeling (OLTP and OLAP/Data Warehousing).
- Advanced Database Programmability: Write, debug, and optimize complex Stored Procedures, Functions, Triggers, and Views to handle core business logic at the database level.
- Performance Tuning & Indexing: Analyze query execution plans, identify bottlenecks, and implement advanced indexing strategies, partitioning, and query refactoring to ensure sub-second response times.
- Python ETL/ELT Pipelines: Develop, schedule, and maintain scalable data ingestion and transformation pipelines using Python to connect disparate data sources.
- Data Integrity & Governance: Establish constraints, data validation routines, and automated quality checks to guarantee absolute data accuracy.
Required Technical Skills
- Expert-Level SQL & DB Programmability (5+ Years): Mastery of writing complex queries (CTEs, Window Functions, Analytical queries) and server-side logic (Stored Procedures/Functions) in platforms like PostgreSQL, SQL Server, Oracle, or MySQL.
- Advanced Database Optimization: Deep understanding of how databases work under the hood—specifically indexing (B-Tree, Hash, Clustered/Non-Clustered), execution plans, statistics, and locking/concurrency mechanisms.
- Python for Data Ingestion (3+ Years): Proficient in writing clean, modular Python scripts for data manipulation, API integration, and ETL processing (using libraries like Pandas, SQLAlchemy, or custom database connectors).
- Data Modeling Methodologies: Practical experience designing Star/Snowflake schemas, Normalization (3NF), and handling Slowly Changing Dimensions (SCD).
Remote & Soft Skills
- Autonomous Execution: Proven ability to manage your own time, architecture tasks, and deliverables without micromanagement.
- Asynchronous Communication: Exceptional written and verbal English communication skills to collaborate seamlessly across time zones.
- Legacy Refactoring Mindset: You enjoy opening up a massive, poorly optimized 500-line stored procedure and refactoring it for 10x performance.
Nice-to-Haves
- Experience migrating legacy on-premise stored procedures to modern cloud data warehouses (Snowflake, BigQuery, Redshift).
- Familiarity with workflow orchestration tools like Apache Airflow or Prefect.
- Experience with dbt (data build tool).
Work Location: Remote

About Mango Sciences
About
Mango Sciences is a leading emerging market data science company connecting millions of underrepresented patients to precision medicine. The company’s Querent™ platform utilizes industry-leading AI analytics to transform deep clinical data into key insights that drive global health improvements. Mango Sciences is currently partnering with hospitals to understand the health data of individuals in India and other emerging markets to drive advancement in patient care and drug discovery for all populations.
Website- https://mangosciences.com/
Industry- Health Technology
Headquarters - Boston, Massachusetts
Tech stack
Similar jobs (10)
Hiring: ETL Developer – Hadoop & PySpark
Location: Bangalore
Experience: 6–10 Years
Budget: 25–30 LPA
Work Mode: Weekdays
Job Description
We are looking for an experienced ETL Developer with strong expertise in Hadoop, PySpark, Python, and SQL to design, develop, and optimize data processing and transformation solutions. The ideal candidate should have hands-on experience working with big data technologies, building scalable ETL pipelines, and managing data for data warehousing and analytics.
Key Responsibilities
- Design, develop, and maintain scalable ETL pipelines for large-scale data processing.
- Develop data transformation workflows using PySpark and Python.
- Work with Hadoop and other big data technologies to process and manage large datasets.
- Write complex SQL queries for data extraction, transformation, validation, and analysis.
- Implement data cleansing, data quality checks, and data validation processes.
- Develop and optimize data integration workflows for data warehousing solutions.
- Troubleshoot ETL failures, performance issues, and data discrepancies.
- Optimize PySpark jobs and SQL queries for performance and scalability.
- Collaborate with data engineers, architects, analysts, and other stakeholders to deliver reliable data solutions.
- Ensure data accuracy, consistency, and adherence to established data governance standards.
Mandatory Skills
- Strong hands-on experience in ETL development.
- Good experience with Hadoop and big data technologies.
- Proficiency in PySpark and Python programming.
- Strong SQL skills, including complex queries and data manipulation.
- Experience in data processing, data transformation, and data integration.
- Understanding of data warehousing concepts and architecture.
- Experience in developing, debugging, and optimizing ETL pipelines.
Required Experience
- 6–10 years of relevant experience in ETL development and data engineering.
- Practical experience handling large datasets using Hadoop and PySpark.
- Strong analytical, problem-solving, and troubleshooting skills.
- Ability to work independently and collaborate effectively within a team.
Interested candidates can share their updated resumes along with current CTC, expected CTC, notice period, and total relevant experience.
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
Job Description
We are looking for an experienced ETL Developer with strong expertise in ETL development, Hadoop, PySpark, Python, and SQL. The candidate should have hands-on experience in developing data pipelines, processing and transforming large datasets, and working with data warehousing and big data technologies.
Key Responsibilities
- Design, develop, and maintain ETL processes and data pipelines.
- Work with Hadoop and PySpark to process and transform large volumes of data.
- Develop and optimize Python scripts for data processing and automation.
- Write complex SQL queries for data extraction, transformation, and validation.
- Perform data cleansing, integration, transformation, and validation.
- Work with data warehousing concepts and large-scale data processing systems.
- Optimize ETL workflows for performance, scalability, and reliability.
- Troubleshoot data pipeline failures and resolve data quality issues.
- Collaborate with data engineers, analysts, and other technical teams.
- Follow data governance, quality, and development best practices.
Required Skills
- Strong experience in ETL Development – Mandatory
- Hands-on experience with Hadoop – Mandatory
- Strong experience in PySpark – Mandatory
- Good programming skills in Python – Mandatory
- Strong knowledge of SQL – Mandatory
- Experience in Data Processing and Transformation – Mandatory
- Knowledge of Data Warehousing – Mandatory
- Experience with Big Data Technologies – Mandatory
Opportunity Details
Role: ETL Developer – Hadoop & PySpark
Experience: 6–10 Years
Location: Bangalore
Mandatory Skills
ETL Development | Hadoop | PySpark | Python | SQL | Data Processing & Transformation | Data Warehousing | Big Data Technologies
About Solutionara
Solutionara is an AI-led IT Consulting and Technology Services organization delivering enterprise transformation through Cloud, Integration, Data Engineering, Digital Experience, AI, and Enterprise Applications.
Headquartered in the United States with a Global Delivery Center (GDC) in Noida, India, Solutionara partners with enterprise organizations across retail, manufacturing, distribution, consumer goods, and other industries to design, implement, and support scalable technology solutions.
As a rapidly growing consulting organization, we foster a culture of ownership, innovation, collaboration, and continuous improvement, empowering our teams to contribute beyond their immediate responsibilities while delivering exceptional value to our global clients.
Every team member is expected to think like a consultant and business problem solver—understanding client objectives, challenging assumptions when appropriate, leveraging AI responsibly, and continuously identifying opportunities to improve quality, productivity, and customer outcomes.
AI is embedded into how we work, but it is an enabler—not a replacement for expertise, critical thinking, or accountability.
Role Overview
Solutionara is seeking a Senior Data Engineer with strong data engineering and database expertise to design, build, optimize, and support enterprise-scale data solutions.
This is a hands-on engineering position requiring strong SQL, Python, ETL/ELT, database, cloud, and troubleshooting capabilities. The engineer will work closely with technical leads and client stakeholders while taking ownership of major engineering components.
Location: Noida, India – Onsite | Employment Type: Full-Time | Experience: 6–9 Years
Key Responsibilities
Data Engineering
- Design, develop, test, deploy, and support scalable ETL/ELT pipelines.
- Build ingestion and transformation solutions across databases, APIs, files, and enterprise applications.
- Develop high-quality SQL and Python-based data processing solutions.
- Implement batch and incremental data-processing patterns.
- Develop reusable engineering components and frameworks.
- Support complex data migration and transformation activities.
- Perform source-to-target mapping and technical data analysis.
- Implement pipeline logging, monitoring, exception handling, and recovery mechanisms.
Database & Platform Engineering
- Design and optimize relational database schemas and data structures.
- Analyze and improve SQL/query performance.
- Support indexing, partitioning, storage optimization, and database performance.
- Implement appropriate database security and access controls.
- Support database monitoring, availability, backup/recovery, and operational requirements in collaboration with infrastructure/platform teams.
- Troubleshoot database and pipeline performance issues.
- Contribute to cloud data-platform configuration and optimization.
Data Quality
- Implement automated validation and data-quality controls.
- Develop reconciliation processes between source and target systems.
- Identify duplicate, incomplete, inconsistent, and invalid data.
- Implement cleansing, standardization, validation, and exception-management logic.
- Work with technical and business stakeholders to understand and implement business data rules.
Technical Delivery
- Convert technical designs into reliable production solutions.
- Participate in technical design and code reviews.
- Mentor junior/mid-level engineers.
- Support estimation and technical planning.
- Troubleshoot complex production and integration issues.
- Collaborate with technical leads, application teams, DevOps, QA, BI, and client teams.
- Document technical designs, mappings, configurations, operational procedures, and engineering decisions.
Consulting & AI-Led Working
- Understand the business purpose behind assigned engineering requirements.
- Raise risks, assumptions, dependencies, and potential improvements proactively.
- Communicate effectively with client and internal stakeholders.
- Use AI-assisted tools to improve coding, testing, analysis, documentation, and troubleshooting productivity.
- Independently verify AI-generated code and recommendations before implementation.
- Identify opportunities for engineering automation and process improvement.
Required Qualifications
- 6–9 years of experience in data engineering, database engineering, data integration, or related areas.
- Advanced SQL skills.
- Strong hands-on Python experience.
- Strong ETL/ELT development experience.
- Strong relational database knowledge, such as SQL Server, PostgreSQL, Oracle, or equivalent.
- Experience with data modeling and database design.
- Experience with AWS, Azure, or another major cloud platform.
- Experience with modern data technologies such as Databricks, Snowflake, Redshift, Synapse, Glue, ADF, Airflow, dbt, or equivalent.
- Experience with performance tuning and optimization.
- Experience with data validation and reconciliation.
- Strong troubleshooting and analytical skills.
- Ability to take ownership of engineering deliverables with limited supervision.
Preferred Qualifications
- Experience working with enterprise ERP, CRM, PIM, PLM, MES, or related systems.
- Experience with manufacturing, retail, distribution, or consumer-goods data.
- Experience with CI/CD and infrastructure/platform engineering practices.
- Experience with API and event-driven integrations.
- Previous consulting or technology-services experience.
What Success Looks Like
- Pipelines and databases perform reliably at enterprise scale.
- Engineering solutions are maintainable, reusable, and well documented.
- Data issues are detected and addressed systematically.
- Junior engineers receive effective technical guidance.
- Problems are owned through resolution rather than simply escalated.
- Engineering decisions reflect both technical requirements and client business objectives.
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
Dear Candidate,
Thanks for showing interest in the opportunity!!!
As discussed, we have an opening for ETL Developer – Hadoop & PySpark with Mphasis for the Bangalore location – Permanent.
Job Description:
We are looking for an experienced ETL Developer with strong expertise in ETL development, Hadoop, and PySpark. The candidate should have hands-on experience in data processing, building and maintaining ETL pipelines, data transformation, and handling large datasets using Big Data technologies.
Primary & Mandatory Skills:
- ETL Development
- Hadoop / HDFS
- PySpark / Apache Spark
- Data Extraction, Transformation & Loading
- SQL and Data Processing
Good to Have:
- Hive / Spark SQL
- Data Pipeline Development
- Big Data Processing
- Python Programming
Company: Mphasis
Role: ETL Developer – Hadoop & PySpark
Experience: As per requirement
Location: Bangalore
Employment Type: Permanent
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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.
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
🚨 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
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.









