Data Engineering Lead

eClerx Services•New York, NY

57d•$220 - $250

About The Position

We are seeking a Data Engineering Lead with a rich experience in designing and implementing data-driven solutions and strategies. This role requires a seasoned professional who can drive data architecture strategies, ensure the scalability of data systems, and work closely with C-suite leadership to align business and data solutions. The ideal candidate will possess a deep understanding of data platforms, cloud computing, data governance, and cutting-edge analytics technologies. The role requires a blend of technical acumen and strategic leadership, making it ideal for an expert with substantial senior management experience

Requirements

At least 15+ years experience in data architecture and solution design.
Proven track record of leading large-scale data-driven transformations and strategic data initiatives in complex environments.
Strong background in designing enterprise-level data architectures and analytics solutions.
Extensive experience working with senior leadership and cross-functional teams.
Valid work authorization in the US
Deep knowledge of data platforms, including relational, NoSQL, and distributed data stores.
Expertise in cloud-based data platforms such as AWS, Azure, or GCP.
Familiarity with big data technologies (e.g., Hadoop, Spark) and modern data pipelines (ETL, ELT).
Proficient in data modeling, data integration, and data visualization tools.
Strong understanding of data privacy, security, and governance best practices.
Exceptional leadership, mentoring, and team-building skills.
Outstanding communication and presentation abilities, with experience presenting to C-level executives.
Strong business acumen with a focus on delivering data solutions that drive business value.
Strategic thinker with the ability to balance innovation with practical, business-oriented solutions.
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.

Nice To Haves

Relevant certifications in data architecture, cloud platforms, or enterprise architecture (e.g., TOGAF, AWS Certified Solutions Architect).
Experience with AI/ML technologies and their application in data-driven business solutions.
Proven ability to influence at the senior management level and lead complex, cross-functional initiatives

Responsibilities

Architecting Data Solutions:
Lead the design, architecture, and implementation of complex data solutions, ensuring scalability, security, and optimal performance.
Develop high-level architecture frameworks and create detailed design specifications for large-scale, high-volume data systems.
Architect data pipelines, databases, and analytic solutions that align with the organization's long-term strategy.
Champion cloud-based and on-premises solutions, with expertise in platforms like AWS, Azure, GCP, and hybrid architectures.
Strategic Leadership:
Collaborate with senior leadership and business stakeholders to define data-driven objectives and craft tailored solutions that meet business needs.
Provide strategic guidance on data architecture, analytics, and business intelligence technologies.
Influence decision-making at the executive level by offering innovative data strategies and solutions aligned with organizational goals.
Act as a trusted advisor to senior leadership, identifying opportunities for data monetization and value generation.
Data Governance & Compliance:
Lead the development and enforcement of data governance frameworks, ensuring compliance with data privacy and security regulations.
Work with legal and compliance teams to ensure all data initiatives meet the necessary standards.
Oversee the management and documentation of data standards, policies, and best practices.
Innovation & Technology Leadership:
Stay ahead of emerging data technologies, including machine learning, AI, and big data analytics, and provide recommendations on their integration.
Evaluate and recommend new tools, technologies, and approaches to optimize data operations and analytics capabilities.
Actively promote data innovation, guiding the team on evolving technologies and methodologies.
Team & Stakeholder Management:
Mentor and lead a team of architects, engineers, and analysts, fostering a culture of innovation and continuous improvement.
Provide leadership and technical expertise to cross-functional teams during the development and implementation of data solutions.
Build and maintain strong relationships with key stakeholders, including senior executives, product managers, and business leaders.
Budgeting and Resource Management:
Oversee the budget and resource allocation for data architecture and solution initiatives.
Drive efficiency in data operations while ensuring high standards of quality.