Maersk Recruitment Drive; Hiring Associate Data Engineer – Apply Now

Associate Data Engineer Job Openings in Pune 2026!!!

Maersk announced job vacancy for the post of Associate Data Engineer. The place of posting will be at Pune (Hybrid), making it suitable for candidates looking for associate data engineer jobs in Pune with flexible work options. Candidates who have completed Graduate / Engineering / Post Graduate with Fresher / Experience are eligible to apply. More details about qualifications, job description and roles & responsibilities are as follows

Company Overview

Name of the Company	Maersk
Required Qualifications	Graduate / Post Graduate
Skills	Data modeling, pipelines, batch/streaming (Kafka, Spark, Flink, or similar)
Category	Technology
Work Type	Hybrid

They are seeking a highly skilled Data Engineer with deep expertise in data engineering concepts, cloud platforms, engineering and operational excellence, and ML Ops practices, aligning with a modern cloud data engineer role in a global organization. The candidate will play a key role in designing, building, and optimizing scalable data infrastructure, enabling efficient data flows across the organization, and supporting machine learning initiatives.

Job Details

Θ Positions: Associate Data Engineer

Θ Job Location: Pune (Hybrid)

Θ Salary: As per company standards

Θ Job Type: Full Time

Θ Requisition ID: R163935

Roles and Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes to process structured and unstructured data as part of a data engineering associate position.
• 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 stakeholders to deliver high-quality, production-ready 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 (CI/CD, testing frameworks, code reviews, performance optimization) to ensure reliability and maintainability of data workflows.
• 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 within a hybrid data engineer job environment.
• Contribute to internal standards, documentation, and guidelines for data engineering excellence.

Required Skills & Qualifications:

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

Preferred Qualifications

• Experience in designing large-scale data platforms serving both analytics and AI/ML needs.
• Exposure to real-time streaming architectures.
• Familiarity with DevOps principles in the context of data and machine learning workflows.
• Strong problem-solving skills, with an emphasis on scalability and reliability.
• Excellent communication skills and ability to work in cross-functional, global teams.

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Disclaimer:

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