Maersk Recruitment 2026 – Associate Data Engineer in Pune

Maersk Off Campus 2026:

Responsibilities of Associate:

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows for structured and unstructured data.
• Implement robust data models, data lakes, and data warehouses that enable analytics and machine learning use cases.
• Collaborate with software engineers, data scientists, and business teams to deliver production-grade data solutions.
• Ensure data quality, governance, and lineage tracking across all data assets.
• Drive operational excellence through automation, monitoring, and alerting for data systems.
• Apply engineering best practices such as CI/CD, testing frameworks, code reviews, and performance optimization.
• Partner with ML engineering and research teams to establish ML Ops pipelines, ensuring reproducibility, model deployment, monitoring, and scalability in production environments.
• Optimize cloud-based data platforms (e.g., AWS, Azure, GCP) for cost, performance, and security.
• Contribute to internal standards, documentation, and guidelines for data engineering excellence.

Maersk Off Campus- Eligibility Criteria:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related discipline.

Required skills:

• Strong foundation in data engineering concepts: data modeling, pipelines, batch/streaming (Kafka, Spark, Flink, or similar).
• Proficiency in cloud services (AWS, Azure, or GCP) with solid experience in cloud-native data tools (e.g., BigQuery, Redshift, Synapse, Databricks, Snowflake).
• Hands-on expertise with modern data orchestration frameworks (Airflow, Prefect, Dagster).
• Strong coding skills in Python, SQL, and one additional language (Scala/Java preferred).
• Experience with engineering excellence practices: version control, CI/CD, unit/integration testing, observability, and performance optimization.
• Background in operational excellence methodologies (SRE principles, system reliability, monitoring, alerting).
• Familiarity with ML Ops frameworks (MLflow, Kubeflow, Vertex AI, or Azure ML) and ability to work closely with ML engineers.
• Understanding of containerization and orchestration (Docker, Kubernetes).
• Knowledge of data governance and compliance best practices (security, access management, GDPR/PII handling).

Click here for HR Interview Questions and Answers

Maersk Recruitment Selection Process:

The selection process is a structured series of stages designed to identify and hire the most suitable candidates for various roles within the company. Here is an overview of the typical selection process:

1. Online Application: The process begins with candidates submitting their applications through the official careers website
2. Resume Screening: The Company’s recruitment team reviews the applications and resumes to assess whether candidates meet the basic qualifications and requirements for the position.
3. Online Assessments: Depending on the role, candidates may be required to complete online assessments or tests to evaluate their technical skills, knowledge, and problem-solving abilities.
4. Technical Interviews: For technical positions, candidates typically participate in one or more technical interviews.
5. Offer: Candidates who successfully complete all interview stages and reference checks will receive a formal job offer.
6. Background Check: Candidates who accept the offer may undergo a background check as part of the final hiring process.
7. Onboarding: After accepting the offer and completing all pre-employment checks, candidates will participate in the onboarding process. This includes orientation, training, and integration into the team.

Please note that the specific details of the selection process may vary based on the role, location, and the hiring team’s preferences. It’s essential for candidates to carefully review the job description and follow any instructions provided during the application process. Preparation for technical interviews and assessments is crucial to excel in the selection process.