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Randstad Digital is seeking a Junior Data Engineer / Software Engineer to support data pipelines, ETL processes, and cloud-based solutions. The role involves API integrations (REST/GraphQL), reporting platforms, and collaboration with data engineers, software engineers, and business stakeholders.
The candidate should be proficient in Python, SQL, and Java, with experience in AWS/Azure, SSIS, Tableau, and Power BI.
We are seeking a Junior Data Engineer / Software Engineer to support data pipelines, ETL processes, cloud-based solutions, software services, API integrations, and reporting platforms. The role requires working knowledge of Python, SQL, Java, AWS, REST APIs, and GraphQL APIs, along with familiarity with relational and non-relational databases. Experience with Azure, SSIS, Tableau, Power BI, GitHub, and AI-assisted development tools such as GitHub Copilot is preferred. The ideal candidate is analytical, collaborative, detail-oriented, and eager to grow in both data engineering and software engineering. ROLE OVERVIEW Seeking a Junior Data Engineer / Software Engineer to support the development, integration, and maintenance of data pipelines, software services, cloud-based solutions, APIs, and reporting platforms. The successful candidate will work with data engineers, software engineers, data architects, analysts, and business stakeholders to extract, transform, validate, and move data across relational and non-relational systems. The role will also support the development and consumption of REST and GraphQL APIs.
Develop, maintain, and support data pipelines and ETL/ELT processes using Python, SQL, AWS, Azure, and SSIS.
Extract, transform, validate, and load data across multiple source and target systems.
Support cloud-based data engineering solutions using AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, Amazon RDS, and CloudWatch.
Write and optimize SQL queries, stored procedures, views, and data transformation logic.
Support data integration across relational and non-relational databases.
Assist with data modeling, data warehousing, data marts, schemas, and dimensional models.
Develop, integrate, test, and support software services using Java and Python.
Develop and consume REST APIs, including working with HTTP methods, authentication, JSON, request and response handling, error handling, and API documentation.
Develop and consume GraphQL APIs, including queries, mutations, schemas, resolvers, and integrations with downstream systems.
Support API integrations between internal applications, data platforms, and external services.
Monitor data pipelines, APIs, and applications, and assist with troubleshooting performance, data quality, and processing issues.
Develop and maintain reports and dashboards using Tableau and Power BI.
Use Git and GitHub for source-code management, version control, collaboration, and pull requests.
Participate in testing, code reviews, deployment, and production support activities.
Document data flows, API specifications, transformation rules, technical processes, and operational procedures.
Use approved AI-assisted development tools, including GitHub Copilot and AI agents, in accordance with client’s security, confidentiality, and responsible-use requirements.
Collaborate with senior engineers, architects, analysts, and business stakeholders to deliver reliable and maintainable solutions.
Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related field. Equivalent practical experience may be considered.
Approximately 0-2 years of experience in data engineering, software engineering, application development, database development, or a related discipline.
Working knowledge of Python, SQL, and Java.
Foundational knowledge of AWS cloud services and cloud-based data or application engineering.
Familiarity with relational database concepts, including tables, keys, joins, indexes, views, and normalization.
Basic understanding of ETL/ELT processes, data pipelines, and data integration.
Foundational understanding of REST APIs and web-service integration.
Awareness of GraphQL concepts, including schemas, queries, mutations, and API integration.
Familiarity with software development practices, including testing, debugging, code reviews, documentation, and version control.
Familiarity with Git and GitHub.
Strong analytical, problem-solving, communication, and collaboration skills.
Hands-on experience with AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, Amazon RDS, and Amazon CloudWatch.
Experience with Microsoft Azure data services.
Experience with SQL Server Integration Services, or SSIS.
Familiarity with non-relational databases, including DynamoDB, MongoDB, or other NoSQL platforms.
Experience designing, developing, testing, or consuming REST APIs.
Experience with GraphQL schemas, queries, mutations, resolvers, or client integrations.
Familiarity with API testing and documentation tools such as Postman, Swagger, or OpenAPI.
Experience with Java frameworks such as Spring or Spring Boot.
Experience developing reports or dashboards using Tableau or Power BI.
Exposure to data warehousing, dimensional modeling, data architecture, JSON, XML, and semi-structured data.
Familiarity with CI/CD, containerization, monitoring, and cloud deployment practices.
Experience using GitHub Copilot, AI agents, or other approved AI-assisted engineering tools.
Python
Java
SQL
AWS
REST APIs
GraphQL APIs
Relational and non-relational databases
ETL/ELT development
SSIS
Azure
Data modeling and data warehousing
Git and GitHub
Tableau and Power BI
API testing and documentation
GitHub Copilot and AI agents
Engineering mindset and willingness to learn.
Strong analytical and problem-solving skills.
Understanding of data quality, accuracy, security, and governance.
Ability to collaborate with technical and non-technical stakeholders.
Clear written and verbal communication.
Attention to detail and commitment to quality.
Ability to learn new technologies, programming languages, APIs, and cloud platforms.
Responsible use of AI-assisted development tools and protection of confidential information.
Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related field. Equivalent practical experience may be considered.
Approximately 0-2 years of experience in data engineering, software engineering, application development, database development, or a related discipline.
Working knowledge of Python, SQL, and Java.
Foundational knowledge of AWS cloud services and cloud-based data or application engineering.
Familiarity with relational database concepts, including tables, keys, joins, indexes, views, and normalization.
Basic understanding of ETL/ELT processes, data pipelines, and data integration.
Foundational understanding of REST APIs and web-service integration.
Awareness of GraphQL concepts, including schemas, queries, mutations, and API integration.
Familiarity with software development practices, including testing, debugging, code reviews, documentation, and version control.
Familiarity with Git and GitHub.
Strong analytical, problem-solving, communication, and collaboration skills.
Hands-on experience with AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, Amazon RDS, and Amazon CloudWatch.
Experience with Microsoft Azure data services.
Experience with SQL Server Integration Services, or SSIS.
Familiarity with non-relational databases, including DynamoDB, MongoDB, or other NoSQL platforms.
Experience designing, developing, testing, or consuming REST APIs.
Experience with GraphQL schemas, queries, mutations, resolvers, or client integrations.
Familiarity with API testing and documentation tools such as Postman, Swagger, or OpenAPI.
Experience with Java frameworks such as Spring or Spring Boot.
Experience developing reports or dashboards using Tableau or Power BI.
Exposure to data warehousing, dimensional modeling, data architecture, JSON, XML, and semi-structured data.
Familiarity with CI/CD, containerization, monitoring, and cloud deployment practices.
Experience using GitHub Copilot, AI agents, or other approved AI-assisted engineering tools.
Python
Java
SQL
AWS
REST APIs
GraphQL APIs
Relational and non-relational databases