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Senior Database Administrator

Maersk
IND
Full-time
Senior · 5+ years experience
Onsite
Discovered 1 weeks ago
awsazurehadooppowershellpythonspark

Full Job Posting

Key Responsibilities:

  • Architect, implement, and manage Microsoft SQL Server platforms (2012 onwards), including availability groups and disaster recovery strategies.
  • Plan and execute database migrations to Azure and AWS PaaS, including minimizing downtime and risk during transitions.
  • Monitor database and infrastructure performance using Prometheus and Grafana; establish dashboards and alerts to proactively detect issues.
  • Automate routine DBA duties such as backups, patching, health checks, and index/statistics maintenance using scripting or orchestration tools.
  • Troubleshoot and resolve complex issues: deadlocks, hung sessions, process blocking, performance bottlenecks, disk I/O or memory/CPU issues.
  • Establish robust security practices: user/role management, encryption at rest/in transit (TDE, backup encryption) where required, auditing, and compliance with relevant standards.
  • Collaborate with a globally distributed team of developers, network and infrastructure engineers, and tech leaders.
  • Develop and maintain runbooks, knowledge base content, playbooks, and documentation to support operations and onboarding.
  • Participate in an on-call rotation to ensure 24/7 availability for mission‐critical systems.

Required Qualifications:

  • 5+ years of experience administering SQL Server in enterprise production environments.
  • Routine availability for at least 2 hours between 8 AM and 5 PM US Central Time Zone.
  • Hands-on experience with database migrations and management in Azure and/or AWS cloud environments.
  • Strong T-SQL and PowerShell skills.
  • Deep understanding of backup/recovery strategies, high-availability setups, replication, and performance tuning.
  • Excellent troubleshooting skills and the ability to resolve performance and availability issues.
  • Effective written and verbal communication, with an emphasis on documentation and cross-team collaboration.

Preferred Qualifications:

  • Certifications in AWS, Azure, or Microsoft SQL Server.
  • Experience with DevOps automation such as CI/CD pipelines.
  • Experience mentoring junior DBAs or developing internal training.
  • Cloud spending optimization skills.
  • General Info:
  • Note that this is a fully onsite role.
  • 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, color, 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.
  • We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing [email protected].
  • 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.
  • CORE SKILLS Data Integration and ETL (Extract, Transform, Load) practices: Combining data from different sources into a single, unified view, and the process of extracting data from sources, transforming it into a suitable format, and loading it into a destination system. Proficiency Level: Advanced Data Analysis: The process of inspecting, cleansing, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making Proficiency Level: Proficient Data Processing Frameworks: Tools and libraries used to process large data sets efficiently, such as Apache Hadoop and Apache Spark. Proficiency Level: Proficient Programming: Writing code to manipulate, analyze, and visualize data, often using languages like Python, R, and SQL. Proficiency Level: Proficient Data Modelling: The process of creating a data model for the data to be stored in a database, representing the data structures and their relationships. Proficiency Level: Proficient Data Quality Management: Ensuring that data is accurate, complete, reliable, and relevant for its intended use. Proficiency Level: Advanced SPECIALIZED SKILLS Data Management: The development and execution of architectures, policies, practices, and procedures to manage the data lifecycle needs of an enterprise. Big Data Technologies: Tools and techniques used to process and analyze large and complex data sets that traditional data-processing software cannot handle Database Design and Management: The process of designing, implementing, and maintaining a database system to ensure data is stored efficiently and securely. Data Visualization: The graphical representation of data to help people understand complex data sets and derive insights. Data Security: Protecting data from unauthorized access, use, disclosure, disruption, modification, or destruction. Data Storage solutions: Systems and technologies used to store data, such as databases, data warehouses, and cloud storage. Data Governance and Compliance: The management of data availability, usability, integrity, and security in an organization, based on internal data standards and policies. Ensuring that an organization adheres to external regulations and internal policies, managing risk, and maintaining ethical standards Technical Documentation: Creating and maintaining documentation that explains the functionality, use, and maintenance of software or systems. Data Architecture: The design and structure of data systems, ensuring that data is stored, managed, and utilized efficiently CI/CD & Observability: The use of continuous integration and continuous delivery (CI/CD) pipelines to automate the process of software development, including building, testing, and deploying code Definition of Proficiency Levels: Foundational: This is the entry level of the skill, typically expected when starting a new role or working with the skill for the first time. You rely on strong manager support, coaching, and training as you build the capability to progress to higher proficiency levels. Proficient: This is the level at which you are considered effective in the skill. You demonstrate more than just functional competence—you begin to have a noticeable impact in your role by applying the skill consistently and meaningfully. You require only minimal support, coaching, or training to apply the skill successfully. Advanced: This is the level where you move beyond meeting expectations to actively leading, influencing, and delivering considerable impact across the wider business. You are seen as a role model, demonstrate the skill independently, and require little to no manager support.

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