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Data Engineer – Early Careers / Trainee

RackspacePosted 6/11/2025

Rackspace logo

Data Engineer – Early Careers / Trainee

Rackspace

Job Location

Job Summary

We are seeking a motivated Fresher/Trainee Data Engineer to join our Cloud Data Services team. As a trainee, you will learn and contribute to the design, development, and maintenance of data pipelines that enable analytics and business decision-making in cloud and hybrid environments. You will assist in developing and maintaining scalable and efficient data pipelines under the guidance of senior engineers. This role is ideal for recent graduates or entry-level candidates passionate about data and cloud technologies. You will have opportunities to work with cross-functional teams, including data scientists, analysts, and business stakeholders. Our team values strong analytical and problem-solving skills, eagerness to learn new technologies, and good written and verbal communication. As a trainee, you will gain hands-on experience with cloud-based data platforms, exposure to real-world data engineering projects, training in ETL pipelines, data modeling, and cloud data services. You may also have the opportunity to transition to a full-time Data Engineer role based on performance. We offer flexible remote work options, $4,000/year travel stipends, and equity in a fast-growing company. Apply now and join our team of passionate professionals who are shaping the future of AI!

Job Description

Job Description: Data Engineer – Early Careers / Trainee
Location:
India – Gurgaon
Immediate joiners only
Department:
Public Cloud – Offerings and Delivery – Cloud Data Services / Hybrid
Job Summary:
We are looking for a motivated Fresher/Trainee Data Engineer to join our Cloud Data Services team. As a trainee, you will learn and contribute to the design, development, and maintenance of data pipelines that enable analytics and business decision-making in cloud and hybrid environments. This role is ideal for recent graduates or entry-level candidates passionate about data and cloud technologies.
Key Responsibilities:
·       Assist in developing and maintaining scalable and efficient data pipelines under the guidance of senior engineers.
·       Support data extraction, transformation, and loading (ETL/ELT) processes.
·       Learn and apply data quality, governance, and validation practices.
·       Participate in developing data models for structured and semi-structured data.
·       Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders.
·       Follow best practices in version control (Git) and Data pipelines /DevOps/MLOps principles.
·       Document data workflows, pipelines, and learnings for future reference.
·       Stay updated with new data engineering tools and technologies.
Education & Qualifications:
·       Bachelor’s Degree (or final year) in Computer Science, Information Technology, Data Engineering, or related fields.
·       Coursework or academic projects in Databases, Data Warehousing, Data Structures, Python/Java/Scala, and SQL.
·       Familiarity with Cloud Platforms (AWS, Azure, or Google Cloud) is a plus.
·       Knowledge of ETL processes, Data Modeling concepts, or Big Data technologies is desirable (Hadoop, Spark).
Technical Skills (Good to Have / Will Learn On-the-Job):
·       Basic knowledge of Python or SQL programming.
·       Exposure to data integration tools or scripting.
·       Understanding of relational and NoSQL databases.
·       Familiarity with data visualization tools like Power BI or Tableau (optional).
·       Interest in Cloud Technologies (AWS S3, Azure Data Lake, GCP BigQuery).
Soft Skills:
·       Strong analytical and problem-solving mindset.
·       Eagerness to learn new technologies and take on challenges.
·       Good written and verbal communication.
·       Ability to work both independently and within a team environment.
·       Attention to detail and time management.
What You Will Gain:
·       Hands-on experience with cloud-based data platforms.
·       Exposure to real-world data engineering projects.
·       Training in ETL pipelines, data modeling, and cloud data services.
·       Opportunity to transition to full-time Data Engineer role based on performance.