Junior Big Data Engineer

N-iX is looking for a Junior Big Data engineer to join our team.

We are seeking a proactive Junior Big Data Engineer to join our team. In this role, you will be responsible for designing, developing, and maintaining scalable data pipelines and reporting-ready data assets within Palantir Foundry. The ideal candidate will possess a robust background in cloud technologies, data architecture, and a passion for solving complex data challenges.

You will collaborate with a cross-functional team and stakeholders to translate business requirements into scalable data solutions, enabling reporting, improving data quality, and driving data transformation initiatives.

Key Responsibilities

• Collaborate with cross-functional teams to gather business requirements and design, implement, and maintain scalable data pipelines in Palantir Foundry, ensuring end-to-end data integrity and optimized workflows.
• Design and maintain data ingestion, transformation, and orchestration pipelines using Palantir Foundry, Python, and PySpark.
• Develop reporting-ready datasets and data models to support downstream analytics and Power BI reporting.
• Develop, optimize, and maintain efficient ETL/ELT processes to collect, process, and integrate data from multiple sources, ensuring timely and accurate data delivery.
• Implement data quality validation, monitoring, and health checks to ensure reliability and consistency of data assets.
• Monitor pipeline performance, identify bottlenecks, troubleshoot production issues, and continuously improve scalability and processing efficiency.
• Plan and prioritize work independently, communicate progress transparently, and proactively manage changing priorities while proposing practical solutions when requirements evolve.
• Maintain clear technical documentation and promote automation and continuous improvement across data engineering processes.
• Stay current with emerging technologies and industry best practices, incorporating innovative approaches into data engineering solutions.

Required Qualifications

•  2+ years of experience in data engineering, preferably within the pharmaceutical or life sciences industry.
• Strong proficiency in Python and PySpark.
• Proficiency with big data technologies (e.g., Apache Hadoop, Spark, Kafka, BigQuery, etc.).
• Hands-on experience with cloud services (e.g., AWS Glue, Azure Data Factory, Google Cloud Dataflow).
• Expertise in data modeling, data warehousing, and ETL/ELT concepts.
• Hands-on experience with database systems (e.g., PostgreSQL, MySQL, NoSQL, etc.).
• Proficiency in containerization technologies (e.g., Docker, Kubernetes).
• Effective problem-solving and analytical skills, coupled with excellent communication and collaboration abilities;

Nice to have

• Experience with market research data
• Familiarity with Veeva CRM, Reltio, SAP, and/or Palantir Foundry
• Background in pharma or healthcare
• Experience with automation / pipeline optimization