Head of Engineering Operations
2 weeks ago
Position: Director of Engineering
Location: Denver, CO | Hybrid - 4 days onsite, 1 day remote
Compensation: $200K - $275K base
Employment Type: Full-Time Direct Hire W2
Collabera is a prominent player in the connected TV (CTV) and cross-screen advertising sector, dedicated to providing cutting-edge advertising solutions that integrate with the rapidly changing digital media landscape.
We are in search of a highly qualified and experienced professional to join our team as the Director of Engineering. The successful candidate will be accountable for steering the strategic direction, development, and management of our data lake infrastructure. This role necessitates a profound understanding of data engineering, exceptional leadership skills, and a proven history of overseeing extensive data environments.
Key Responsibilities:
Strategic Leadership
- Establish and implement the strategic vision for the data lake infrastructure.
- Align data lake projects with the overarching data strategy and business objectives.
- Identify and utilize innovative technologies to enhance data lake functionalities.
- Formulate and execute a strategic vision for business intelligence that aligns with corporate goals.
Team Management
- Guide, mentor, and motivate a team of data engineers, software engineers, and data visualization specialists.
- Cultivate a culture of innovation, teamwork, and continuous enhancement.
- Provide opportunities for professional growth and conduct performance evaluations.
Data Lake Architecture and Development
- Supervise the design, implementation, and upkeep of scalable and secure data lake solutions.
- Ensure the data lake's high availability, scalability, and performance.
- Develop and enforce best practices for data governance, security, and compliance.
Operational Excellence
- Guarantee the efficient and reliable operation of the data lake environment.
- Implement monitoring, logging, and alerting solutions to maintain system health.
- Manage budgets, resources, and timelines for data lake initiatives.
Stakeholder Collaboration
- Collaborate closely with data scientists, analysts, and other stakeholders to comprehend data requirements.
- Facilitate communication between technical teams and business units.
- Translate business needs into technical solutions and project plans.
Innovation and Continuous Improvement
- Stay informed about industry trends, emerging technologies, and best practices in data engineering.
- Drive innovation by identifying opportunities for process enhancements and automation.
- Encourage the adoption of new tools and technologies to improve data lake functionality.
- Promote innovative approaches to business intelligence and analytics using advanced methodologies.
Data Governance
- Identify potential risks associated with data security, privacy, and system performance.
- Develop and implement strategies to mitigate risks.
- Ensure compliance with relevant regulations and standards regarding data governance.
- Implement data quality management processes and tools to monitor and enhance data integrity.
Qualifications:
Education:
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related discipline. Advanced degrees are advantageous.
Experience:
- Proven experience in data engineering, data architecture, or a related field.
- Experience in a leadership or managerial capacity.
- Specific experience in the Advertisement Technology (AdTech) sector.
- Demonstrated success in managing and scaling large data lake environments.
Technical Skills:
- Expertise in big data technologies such as Hadoop, Spark, and NoSQL databases.
- Proficiency in programming languages such as Python, Java, or Scala.
- Extensive experience with cloud platforms (AWS, Azure, Google Cloud) and their data services.
- Strong understanding of data governance, security, and compliance best practices.
Soft Skills:
- Exceptional leadership and team management capabilities.
- Strategic thinking and problem-solving abilities.
- Excellent communication and interpersonal skills.
- Ability to thrive in a fast-paced, dynamic environment.
Preferred Qualifications:
- Experience with machine learning and advanced analytics.
- Knowledge of data Lakehouse architecture in Databricks.
- Experience with CI/CD pipelines and DevOps practices in data engineering.
- Relevant industry certifications in cloud data engineering or architecture.
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