Data Engineer Intern at Springer Capital · Remote only · 0 - 1 years · ₹5000 - ₹7000 / mo · Profitable · Remote only · Posted 12 Jun 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 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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Skills Referential (Required knowledge, skills and abilities)
Technical Skills:
Python
Pyspark
SQL
ETL Aws, Azure, gcp
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
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
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
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.
About Us:
The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
Job Summary:
We are looking for a Senior Data Engineer who is creative, collaborative, and adaptable to join our agile team of data scientists, engineers, and UX developers. The role focuses on building and maintaining robust data pipelines to support advanced analytics, data science, and BI solutions.
As a Senior Data Engineer, you will work with internal and external data, collaborate with data scientists, and contribute to the design, development, and deployment of innovative solutions.
Key Responsibilities:
- Design, develop, test, and maintain optimal data pipeline and ETL architectures.
- Map out data systems and define/design required integrations, ETL, BI, and AI systems/processes.
- Prepare and optimize data for predictive and prescriptive modeling.
- Collaborate with teams to integrate ERP data into the enterprise data lake, ensuring seamless flow and quality.
- Enhance cloud data infrastructure on AWS or Azure for scalability and performance.
- Utilize big data tools and frameworks to optimize data acquisition and preparation.
- Build architectures to move data to/from data lakes and data warehouses for advanced analytics.
- Develop and curate data models for analytics, dashboards, and reports.
- Conduct code reviews, maintain production-level code, and implement testing approaches.
- Monitor, troubleshoot, and resolve data ingestion workflows to maintain reliability and uptime.
- Drive innovation and implement efficient new approaches to data engineering tasks.
Must-Have Skills:
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
- 5+ years of experience working with enterprise data platforms, including building and managing data lakes.
- 3–5 years of experience designing and implementing data warehouse solutions.
- Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
- Proficiency in Spark (Python/Scala) and Spark Streaming for real-time data pipelines.
- Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
- Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
- Hands-on experience with orchestration tools (e.g., Apache Airflow, Prefect).
- Knowledge of CI/CD processes, version control (e.g., Git, Jenkins), and deployment automation.
- Strong problem-solving, communication, and collaboration skills.
Good-to-Have Skills:
- Experience in integrating ERP data into data lakes.
- Experience with traditional ETL tools (e.g., Talend, Pentaho).
Competencies:
- Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
- Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
- Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
- Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
Why Join Us?
- Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
- Work on impactful projects that make a difference across industries.
- Opportunities for professional growth and continuous learning.
- Competitive salary and benefits package.
Application Details
Ready to make an impact? Apply today and become part of the QX Impact team!
What you'll need
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
- 5+ years of professional data engineering experience.
- Experience designing and building cloud-native data solutions.
- Strong expertise with Google Cloud Platform, including BigQuery. Experience developing transformation frameworks using dbt.
- Strong SQL and Python programming skills.
- Experience with PostgreSQL or other relational databases.
- Experience orchestrating workflows using Apache Airflow or Cloud Composer.
- Experience implementing Infrastructure as Code using Terraform. Experience building CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or similar platforms.
- Experience developing scalable batch and streaming data pipelines. Strong problem-solving skills with the ability to balance scalability, reliability, and cloud cost optimization.
Preferred Qualifications
- Experience with Pub/Sub, Datastream, Dataflow, Cloud Storage, Cloud Functions, or Cloud Run.
- Experience building multi-tenant SaaS platforms.
- Experience implementing metadata-driven governance, lineage, and data quality frameworks.
- Experience supporting AI, machine learning, or customer-facing analytics platforms.
- Experience with Kubernetes and Docker.
Location – Hyderabad (Hybrid)
Work Experience – 5 to 7 years
CTC – upto 20 LPA
Roles & Responsibilities:
· We are looking for a Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines.
· Integration of data from multiple sources or vendors to provide the holistic insights from data.
· You are expected to build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms etc.
· Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues.
· Should have experience in client interaction.
· Experience in mentoring juniors and providing required guidance.
Required Technical Skills
· Extensive hands on experience in Python, Pyspark, SQL, Dataiku.
· Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.
· Working knowledge in Databricks, Redshift, ADF etc.
· Hands-on experience in cloud services like Azure, AWS- S3, Glue, Lambda, CloudWatch, Athena.
· Sound knowledge in end-to-end Data management, Data ops, quality and data governance.
· Familiar with SFDC, Waterfall/ Agile methodology.
· Strong domain knowledge in Pharma domain/ life sciences commercial data operations.
Qualifications
· Bachelor’s or master’s Engineering/ MCA or equivalent degree.
· 5-7 years of relevant industry experience as Data Engineer.
· Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.
· High motivation, good work ethic, maturity, self-organized and personal initiative.
· Ability to work collaboratively and providing the support to the team.
· Excellent written and verbal communication skills.
· Strong analytical and problem-solving skills.






