Senior Data Engineer presso Maersk

Maersk Line Fleet Management and Technology is responsible for Ship Management of Maersk Line owned container vessels. As a part of the Energy Transition Transparency and Enablement team you will be responsible for developing the strong enterprise architecture, building effective data pipelines based on ADLS/MIDAS and providing end-to-end support on energy transition projects. In this position, you will play an important role in developing, maintaining and improving complex algorithms from multiple systems / databases for emissions across the Maersk business. You will be working in dynamic work environment with shifting priorities between Operational and Project related work.

Experience: 8+ Years of data engineering

Location: Mumbai

Key Responsibilities

As a Senior Data Engineer, your assignments and projects will typically include:

• Develop algorithms / scripts for emission and fuel consumption performance and optimization for Maersk business.

• Maintenance of existing emission and bunker performance monitoring algorithms / scripts including debugging and improvements.

• Support existing in-house applications and develop new applications to support Maersk’s strategic cost savings target.

• Manage data from multiple systems including Azure systems to enable and facilitate subject matter expertise to deliver Projects.

• Driving deep dive analysis into decarbonization and emission related data

• Bringing forward innovative ideas on how the performance data in our systems along with other Maersk’s systems can support optimization of our fleet.

• Handle ad-hoc data requests from various stakeholders.

• Assist and participate in exploring programming languages such as Python and R for handling big data sets received from Star Connect – Maersk’s auto-logging performance system.

• Ensure strong stakeholder management with Energy Transition team and other departments across Maersk through regular meetings/conference calls.

Who we are looking for

• We are looking for a candidate with 8+ years of data engineering experience, ideally in an analytics intensive environment with working experience using Big data solutions on MS Azure cloud, MIDAS/Pipedream, BI tools (Spark / PySpark / Spark SQL / Scala).

• Experience of delivering end-to-end data solutions, Strong knowledge of Python, SQL / NoSQL databases.

• Experience developing batch / real-time processing solutions by using Azure Data Factory, Azure Databricks and Azure Data Lake source.

• Experience with MIDAS/Pipedream would be preferable:

  • Event-driven integrations across applications and services.

  • Workflow automation for data ingestion, transformation, product development and deployment.

• Experience in working with code versioning tools with ADO GIT repositories, CI/CD pipelines.

• Inclination towards deep dive analysis and adding value with critical insights.

• Exposure to Data science related programming environments like R and Python.

• As a person, you are independent, systematic and detail oriented, with a positive and proactive mind-set towards new tasks, but also comfortable with tasks of a repeatable nature. You are open and willing to take on new learnings, which are outside your comfort zone. You must be an enthusiastic and motivated team player, who understands that a strong team performance achieves the highest goals. You have effective English communication and stakeholder management skills.
  
  
   

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.

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