Manager Data Engineering Operations Position Available In Miami-Dade, Florida
Tallo's Job Summary: The Manager Data Engineering Operations role in Miami, FL involves leading a team to enhance data warehousing and integration capabilities, aligning with organizational goals through DataOps principles and Lean practices. Responsibilities include developing strategies, managing the team, overseeing vendor contracts, ensuring data quality, and implementing improvement plans. The position requires a Bachelor's degree and at least 7 years of relevant experience in data engineering and technology tools.
Job Description
Job ID10968
Location
Miami, FL
Full/Part TimeFull-Time
Regular/TemporaryRegular Responsibilities
JOB SUMMARY
Responsible for leading the Data Engineering Operations team to enhance data warehousing and data integration capabilities while ensuring robust, scalable, and seamless operations. This role drives innovation and aligns team efforts with organizational goals by emphasizing DataOps principles and Lean practices. In addition, the manager ensures that data pipelines, quality controls, and metadata management practices are designed to support evolving advanced analytics initiatives-including AI, ML, and Data Science-to enable the organization to derive actionable insights from high-quality, trusted data.
DUTIES & RESPONSIBILITIES
Develop and implement Data Engineering Operations strategies that integrate DataOps and Lean practices, promoting continuous learning, rapid iteration, and effective communication to achieve organizational goals.
Ensure that data pipelines and processes not only support core enterprise data management needs but also accommodate the evolving requirements of advanced analytics initiatives.
Lead, mentor, and manage the Data Engineering Operations team, fostering a culture of continuous improvement, collaboration, and proactive incident management.
Oversee the negotiation, onboarding, cost optimization, and SLA aspects of vendor products and contracts related to data technology assets.
Establish and monitor performance metrics for data management systems, ensuring reliability and optimal performance through robust automation, monitoring, and observability practices.
Ensure adherence to data governance, privacy, and security standards by incorporating proactive risk management and incident response strategies.
Develop and implement continuous improvement plans for data systems, focusing on process automation and integrating monitoring tools (e.g., SPC) for system performance visibility, while providing on-call support and escalating issues as needed.
Oversee the planning, execution, and delivery of enhancement projects for Data Engineering Operations, ensuring projects meet quality, time, and budget constraints while adhering to DataOps principles.
Work closely with cross-functional teams and up to ten (tri-brand) business stakeholders, ensuring open communication and alignment between traditional data management functions and advanced analytics initiatives.
Leverage DataOps practices, including automated testing, continuous monitoring, and error handling, to ensure high-quality data flows and provide transparency through automated metadata capture and catalog integration.
Design processes that support core operations and advanced analytics initiatives, ensuring AI, ML, and Data Science teams have access to consistent, high-quality data.
Evaluate and implement new technologies and processes to enhance data engineering delivery, while championing automation, rapid iteration, and Lean practices to drive operational excellence and business value.
Perform other job-related functions as assigned.
QUALIFICATIONS DEGREE TYPE
Bachelor’s Degree FIELD(S)
OF STUDY
Business Management, Computer Science, Industrial Engineering, or a related field; or an equivalent combination of education and experience.
EXPERIENCE
Minimum of 7 years’ experience in developing, validating, and implementing data warehouses, data systems, or cloud-based solutions (IaaS, PaaS).
Experience supporting business initiatives through optimized data pipelines and quality processes.
Proficiency with technologies and tools such as Python, PowerShell, Bash (or Spark), SQL, git, Terraform, Puppet, Docker/K8s, and Agile methods & tools like JIRA.
Experience with message brokers such as Event Hubs or Kafka (Confluent).
COMPETENCIES/SKILLS
Strong interpersonal, presentation, and communication skills.
Exceptional analytical and problem-solving abilities with experience managing multiple priorities in a fast-paced environment.
Proven success in driving cross-functional collaboration and delivering operational excellence.
Solid understanding of agile methodologies, QA practices, and user experience, with a focus on digital and technical acumen.
Familiarity with advanced analytics concepts-including AI, ML, and Data Science-and the ability to design data processes that support these initiatives alongside traditional enterprise needs.
Proficiency with collaboration tools (e.g., JIRA, Confluence, Lucidchart) and SQL query tools.
Experience with configuring and managing databases (e.g., Microsoft SQL Server, Oracle, MySQL, HANA, Snowflake, Databricks, etc).
Knowledge of both traditional on-premises and cloud-based infrastructures (preferably AWS), including Windows and Linux-based environments.
Working knowledge of various open-source technologies and cloud services.
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