Marketing Intern at Springer Capital · Remote only · 0 - 1 years · ₹5000 - ₹7000 / mo · Profitable · Remote only · Posted 23 Jul 2026

Springer Capital is a cross-border asset management firm specializing in real estate investment banking between China and the USA. We are offering a remote internship for aspiring data engineers interested in data pipeline development, data integration, and business intelligence.
The internship offers flexible start and end dates. A short quiz or technical task may be required as part of the selection process.
Responsibilities:
- Design, build, and maintain scalable data pipelines for structured and unstructured data sources
- Develop ETL processes to collect, clean, and transform data from internal and external systems
- Support integration of data into dashboards, analytics tools, and reporting systems
- Collaborate with data analysts and software developers to improve data accessibility and performance
- Document workflows and maintain data infrastructure best practices
- Assist in identifying opportunities to automate repetitive data tasks

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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
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
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
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
1st virtual , 2nd round F2F -
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
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
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.
Strong Data Engineer (AWS) Profile
2
Mandatory (Experience 1) – Must have minimum 6+ years of experience in Data Engineering, with strong experience designing, developing, and maintaining scalable data pipelines and ETL processes.
3
Mandatory (Experience 2) – Must have 3+ years of hands-on experience with AWS data engineering services, particularly S3, AWS Glue, EMR, Lambda, and Redshift.
4
Mandatory (Experience 3) – Must have strong programming experience in Python, Java, or Scala, with hands-on development of data processing and pipeline solutions.
5
Mandatory (Experience 4) – Must have strong expertise in SQL, data warehousing, and database technologies, including experience with both SQL and NoSQL databases.
6
Mandatory (Experience 5) – Must have hands-on experience working with Big Data technologies and distributed data processing, including designing and optimizing large-scale data pipelines.
7
Mandatory (Experience 6) – Must have experience with data pipeline troubleshooting, monitoring, data quality, governance, and security best practices.
8
Mandatory (Education) – B.Tech / B.E./ M.Tech
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.
Responsibilities
· Design and build data pipelines and ETL processes to move and transform data reliably across company systems
· Develop and maintain data models that support reliable, well-structured reporting and analytics
· Write and optimise SQL across data pipelines, reporting layers, and ad hoc analysis
· Build and maintain Power BI dashboards and reports that give stakeholders clear, accurate visibility into business performance
· Apply data structures and algorithms thinking to design efficient, scalable data processes
· Apply version control and CI/CD practices to data pipeline and analytics code, ensuring changes are tested and deployed safely
· Apply AI tools and literacy to accelerate data engineering, analysis, and reporting work
· Contribute to data warehouse design, database administration, or solution architecture where relevant
· Work closely with stakeholders across the business to understand reporting needs and translate them into reliable data solutions
Requirements
· Mandatory overlap with Sydney team throughout
. 3 to 6 years of relevant experience
· Strong SQL skills, comfortable writing and optimising complex queries across large datasets
· Solid experience with data modelling, structuring data for reliable and maintainable reporting
· Hands-on experience building data pipelines and ETL processes
· Experience building data visualisations and dashboards, ideally in Power BI
· Good grounding in data structures and algorithms
· Practical experience with version control (e.g. Git) and CI/CD pipelines
· Working AI literacy - comfortable using AI-assisted tools to support data engineering and analysis
· Exposure to Azure, data warehousing, database administration, or solution architecture is an advantage, not a requirement
Analytical and curious, detail-oriented, a strong problem solver who communicates well and can work independently











