|
| 1 | +The responsibilities of the Lead, Data and Analytics are multifaceted and require a strong understanding of both technical and leadership domains: |
| 2 | + |
| 3 | +Technical Leadership and Strategy: The Lead will be at the forefront of designing and developing data and analytics solutions that are in complete alignment with Company's overarching technology strategy. This involves establishing and rigorously enforcing data engineering standards, championing best practices, and defining robust architectural patterns to ensure consistency and efficiency across all data initiatives. A key aspect of this responsibility includes the continuous evaluation of new and emerging technologies, with the expectation to provide well-reasoned recommendations for their adoption when they offer significant benefits to Company's data ecosystem . Furthermore, the Lead will serve as a technical expert, providing invaluable guidance and mentorship to other team members, fostering their growth and ensuring the team remains at the cutting edge of data and analytics practices . The expectation is that this individual will not only possess deep technical knowledge but also the ability to translate that knowledge into actionable strategies that drive the team forward and enhance Company's data capabilities. |
| 4 | + |
| 5 | +Data Engineering and Pipeline Development: A core responsibility involves the hands-on design, construction, and maintenance of robust and scalable data pipelines. These pipelines are critical for the efficient ingestion, seamless processing, and accurate transformation of data from a diverse range of sources. These sources include cutting-edge big data platforms, flexible cloud storage solutions, and established traditional databases, reflecting the complex data landscape of a global financial institution . The Lead will be tasked with optimizing these data pipelines to achieve peak performance, ensuring unwavering reliability, and enabling seamless scalability to handle the ever-increasing volumes of data. Implementing comprehensive data quality checks and proactive monitoring processes will also fall under their purview, guaranteeing the integrity and trustworthiness of the data that powers Company's critical operations and decision-making . The ability to convert legacy SAS-based pipelines into modern languages like PySpark and Scala for execution on both Hadoop and non-Hadoop ecosystems is also a significant aspect of this role, highlighting the need to modernize existing data infrastructure . |
| 6 | + |
| 7 | +Project Management and Delivery: The Lead will be expected to take ownership of data and analytics projects from their initial conceptualization all the way through to their successful completion. This includes ensuring that all projects are delivered not only on time but also within the allocated budget, demonstrating strong financial and resource management skills . A crucial first step involves clearly defining the project scope, establishing measurable objectives, and outlining specific deliverables in close collaboration with all relevant stakeholders, ensuring that everyone is aligned on the goals and expectations. The Lead will also be responsible for proactively identifying and effectively managing any project risks, potential issues, and critical dependencies that could impact the project's trajectory. Adherence to established project management methodologies, such as Agile and SDLC, will be essential to ensure a structured and efficient approach to project execution . A proven track record of successfully managing and implementing data-related projects is a key requirement for this role . |
| 8 | + |
| 9 | +Team Leadership and Mentorship: This role involves providing strong leadership and effective mentorship to a team of talented data engineers and skilled analysts. The Lead will play a crucial role in fostering their professional growth and continuous development, creating an environment where team members can learn, innovate, and excel . Supervising day-to-day staff management responsibilities, including the efficient allocation of resources and the strategic assignment of work, will be a key part of ensuring the team's productivity and effectiveness . The Lead will be instrumental in promoting a collaborative and high-performing team culture, where open communication, mutual respect, and a shared commitment to excellence are paramount . Providing constructive coaching, valuable guidance, and serving as a knowledgeable advisor to junior team members will be essential for nurturing talent and building a strong, capable data and analytics team . This aspect of the role requires not only technical expertise but also strong interpersonal skills and a genuine commitment to the growth and success of the team. |
| 10 | + |
| 11 | +Collaboration and Stakeholder Management: The Lead will be expected to forge strong partnerships with a diverse group of stakeholders, including domain experts who possess deep business knowledge, product managers who define the vision for data products, experienced analysts who derive insights from data, and skilled data scientists who build advanced analytical models . A key responsibility will be to thoroughly understand their unique data needs and to effectively deliver tailored data and analytics solutions that meet those requirements. Excellent communication skills, both written and verbal, are essential for effectively interacting with both technical and non-technical stakeholders, ensuring that complex information is conveyed clearly and concisely . Furthermore, the Lead will collaborate closely with various cross-functional teams across the organization to ensure seamless alignment and effective integration of data and analytics initiatives with broader business objectives, fostering a cohesive and data-driven culture throughout Company . The ability to influence and negotiate with senior leaders will also be important in driving the adoption of data-driven strategies . |
| 12 | + |
| 13 | +Data Quality and Governance: Ensuring the accuracy, integrity, and unwavering reliability of data is a fundamental responsibility of this role. The Lead will be tasked with defining and implementing robust data quality standards and comprehensive processes to maintain the highest levels of data integrity . Adherence to Company's established data governance policies and procedures will be strictly required, ensuring compliance with internal regulations and industry best practices . This involves defining needs around maintainability, testability, performance, security, quality, and overall usability of the data platform . The Lead will play a critical role in establishing a culture of data quality within the team and across the organization, ensuring that data is treated as a valuable asset and that decisions are based on trustworthy information. |
| 14 | + |
| 15 | +Research and Innovation: In the rapidly evolving field of data and analytics, it is crucial to stay informed about the latest trends and advancements in technologies. The Lead will be expected to proactively research and thoroughly evaluate new tools, innovative techniques, and emerging methodologies that have the potential to significantly improve Company's data and analytics capabilities . This includes driving a culture of innovation within the data and analytics function, encouraging experimentation, and championing the adoption of cutting-edge solutions that can provide a competitive edge to the organization. This role requires a forward-thinking individual who is passionate about exploring new possibilities and continuously seeking ways to enhance Company's data-driven capabilities . The evaluation of new IT developments and evolving business requirements, leading to recommendations for appropriate system alternatives or enhancements, is a key aspect of this responsibility . |
| 16 | + |
| 17 | +Risk Management and Compliance: Given that Company operates within the highly regulated financial services industry, a strong understanding of risk management principles and strict adherence to compliance regulations are paramount. The Lead will be responsible for appropriately assessing risk in all business decisions, demonstrating a deep consideration for the firm's reputation and actively safeguarding Companygroup, its clients, and its valuable assets . This involves diligently driving compliance with all applicable laws, relevant rules, and internal regulations, consistently adhering to Company's established policies, and applying sound ethical judgment in all professional conduct. |
| 18 | + |
| 19 | +To be successful in this challenging and rewarding role, candidates should possess the following qualifications: |
| 20 | + |
| 21 | +Technical Skills: A candidate must have extensive hands-on experience with a wide range of big data technologies. This includes a strong understanding of the Hadoop ecosystem, with a preference for experience with Cloudera . Proficiency in Spark, Hive, Impala, Kafka, Kudu, Solr, and Elastic Search is essential . Furthermore, the role requires strong programming skills in languages critical for data engineering, such as Python, Scala, and Java . Practical experience with major cloud platforms, including AWS, Azure, or GCP, is highly desirable, with a preference for candidates who have actively supported deployments on these platforms . Expertise in building robust data pipelines using various ETL/ELT tools and frameworks, such as Apache Nifi, Talend, or Apache Airflow, is a key requirement . A solid understanding of both relational and NoSQL databases is necessary, along with proven experience in data modeling, schema design, and performance optimization . Familiarity with containerization technologies like Docker and Kubernetes, as well as CI/CD practices and automation, is also expected . Finally, a strong grasp of data warehousing concepts and data lake architectures is fundamental , and while not explicitly for engineering roles in the snippets, experience with data visualization tools like Tableau or Power BI could be beneficial given the "Analytics" component of the role . |
| 22 | + |
| 23 | +Experience: Candidates must possess a minimum of 12 years of progressive experience in the IT field, with at least 8 years specifically focused on hands-on work with Hadoop and other big data technologies . A significant portion of their experience should be in the design, development, and successful implementation of complex data pipelines for data ingestion and transformation . Proven experience in leading large-scale data and analytics projects is essential, demonstrating the ability to manage all aspects of the project lifecycle from initiation to completion . Prior experience in team leadership and effective mentorship of technical teams is a critical requirement . Experience within the banking, capital markets, or broader financial services industry is strongly preferred, as it provides valuable context for the specific data challenges and regulatory requirements within Company . Experience with enterprise-scale, multi-region project development is also highly desirable . Prior experience in the conversion of SAS-based pipelines to modern big data technologies would be considered a significant plus , as would any experience in Hadoop administration . |
| 24 | + |
| 25 | +Education: A Bachelor's degree (University degree) in Computer Science, Engineering, Data Science, Analytics, or a closely related field is a mandatory requirement . A Master's degree in one of these fields is highly preferred, as it often indicates a deeper theoretical understanding and advanced analytical capabilities that are valuable for this senior-level role . Equivalent practical experience may be considered in lieu of a Master's degree in exceptional circumstances. |
| 26 | + |
| 27 | +Certifications (Optional but desirable): While not explicitly required, relevant industry certifications can be a significant advantage. These include certifications in leading cloud platforms such as AWS Certified Data Engineer, Azure Data Engineer Associate, or Google Cloud Professional Data Engineer. Similarly, big data certifications, such as Cloudera Certified Data Engineer, can further demonstrate a candidate's specialized knowledge and commitment to the field. |
| 28 | + |
| 29 | +In addition to the necessary technical expertise and professional experience, certain soft skills are crucial for success in this leadership role: |
| 30 | + |
| 31 | +Exceptional written and verbal communication skills are paramount, with the proven ability to clearly and effectively articulate complex technical concepts to a diverse range of audiences, including both technical peers and non-technical business stakeholders . |
| 32 | +Strong problem-solving and analytical skills are essential, with a demonstrated ability to thoroughly analyze intricate issues, identify root causes, and develop practical and effective solutions . |
| 33 | +Proven leadership and team management skills are required, including demonstrable experience in effectively leading, mentoring, and coaching team members to achieve their full potential and contribute to a high-performing team environment . The ability to influence and negotiate with senior leaders is also important . |
| 34 | +Strategic thinking and the capability to align data and analytics initiatives with broader business goals and objectives are critical for driving impactful outcomes and contributing to the overall success of the organization . |
| 35 | +Adaptability and a strong learning agility are necessary to thrive in the ever-evolving landscape of data and analytics technologies, with a proactive willingness to continuously learn and stay updated on the latest trends and advancements . |
| 36 | +Strong collaboration and interpersonal skills are vital for building effective working relationships with diverse teams across the organization, fostering a positive and productive working environment . |
| 37 | +A keen attention to detail and an unwavering commitment to maintaining high standards of data quality and accuracy are essential for ensuring the reliability and trustworthiness of data used for critical decision-making . |
| 38 | +The ability to effectively work under pressure and manage multiple priorities while consistently meeting deadlines is crucial for navigating the demands of a senior-level role in a fast-paced environment . |
| 39 | +Strong organizational and project management skills are necessary for effectively planning, executing, and delivering complex data and analytics projects on time and within budget . |
| 40 | +Company offers a comprehensive and competitive benefits package designed to support the well-being and professional growth of our employees. While specific details for this role in Farmers Branch, TX should be researched on Company's career website, typical benefits for senior-level tech roles often include comprehensive medical, dental, and vision coverage, along with a Health Savings Account option. Employees can also expect life insurance, short-term and long-term disability protection, and paid parental leave. Company provides paid holidays and generous vacation time to ensure employees have ample opportunity for rest and rejuvenation. Retirement savings are supported through a 401(k) plan with a company match, and opportunities for career development and tuition reimbursement are often available to encourage continuous learning and advancement . Exploring Company's specific offerings will provide a complete picture of the rewards and benefits associated with this exCompanyng opportunity. |
| 41 | + |
| 42 | +Company is an equal opportunity employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. |
| 43 | + |
| 44 | +Interested candidates who meet the qualifications outlined above are encouraged to apply through Company's career website. Please refer to the specific job posting for "Lead, Data and Analytics (C13)" in Farmers Branch, TX for detailed application instructions and any relevant deadlines. We look forward to receiving your application. |
| 45 | + |
| 46 | +Summary of Key Technical Skills and Experience Levels |
| 47 | + |
| 48 | +Skill/Technology Minimum Years of Experience Level of Proficiency Frequency of Mention in Company Snippets |
| 49 | +Hadoop 8+ Hands-on, Advanced 3 |
| 50 | +Spark - Hands-on, Expert 4 |
| 51 | +Python - Proficient 3 |
| 52 | +Scala - Proficient 3 |
| 53 | +Java - Proficient 3 |
| 54 | +Cloud Platforms (AWS, Azure, GCP) - Hands-on 1 |
| 55 | +ETL/ELT Tools - Expertise 1 |
| 56 | +SQL - Strong Understanding 1 |
| 57 | +NoSQL Databases - Solid Understanding 1 |
| 58 | +Data Pipelines - Significant Experience 3 |
0 commit comments