ETL Lead

ETL Lead – Drive Data-Driven Innovation in Banking and Technology

Are you a visionary data engineer passionate about transforming raw data into strategic assets? We are seeking an experienced ETL Lead to spearhead the evolution of our enterprise data warehouse (EDW) architecture, optimize our data warehouse (DWH) models, and architect robust data pipelines that empower our organization with actionable insights. In this pivotal role, you will lead the design, implementation, and continuous enhancement of data infrastructure, ensuring seamless integration, real-time processing, and scalability across diverse systems. This is an opportunity to shape the future of data management in a dynamic banking and technology environment while bridging the gap between technical innovation and business strategy.

As the ETL Lead, your expertise will be instrumental in driving efficiency, accuracy, and innovation in our data ecosystem. You will collaborate closely with cross-functional teams, including data architects, business stakeholders, and senior management, to define and execute a cohesive data integration strategy. Your ability to translate complex technical concepts into clear, actionable insights for non-technical audiences—and vice versa—will be critical in aligning data solutions with business objectives. Whether you're optimizing legacy systems, integrating new data sources, or implementing cutting-edge technologies, your leadership will ensure that our data infrastructure remains agile, secure, and aligned with industry best practices.

Key Responsibilities

Your role will encompass a broad spectrum of responsibilities, including but not limited to:

• Architect and Optimize Data Infrastructure: Design, implement, and maintain scalable data pipelines, ETL processes, and data warehousing solutions using advanced technologies and methodologies. Leverage your expertise in dimensional modeling, data quality (DQ), master data management (MDM), and metadata management to ensure data integrity and consistency across systems.
• Lead Data Pipeline Development: Develop, test, and deploy high-performance data workflows, transformations, and integrations to facilitate seamless data extraction, transformation, and loading (ETL/ELT) from disparate sources—both internal and external—to the data warehouse. Utilize tools such as Microsoft SSIS, Talend, Informatica, and SQL to build efficient and reliable pipelines.
• Drive Real-Time Data Processing: Implement and optimize streaming and real-time data processing solutions using technologies like Apache Spark, Kafka, and ksqlDB. Ensure these platforms are deployed following industry best practices to support scalable, low-latency data processing for critical business applications.
• Collaborate with Stakeholders: Act as a bridge between technical and business teams, translating complex data requirements into executable solutions. Engage with senior leadership and middle management to understand reporting, dashboarding, and analytical needs, and advocate for data-driven decision-making that enhances operational efficiency and business outcomes.
• Enhance Data Strategy and Governance: Contribute to the development and refinement of our data management strategy, ensuring alignment with organizational goals. Work closely with data architecture teams to define integration standards, data governance policies, and best practices that foster a culture of data excellence.
• Technical Documentation and Knowledge Sharing: Maintain comprehensive, up-to-date technical documentation to support current and future projects. Share your expertise through mentorship, training, and collaborative sessions to foster a skilled and informed data engineering community.
• Innovate and Adopt New Technologies: Stay ahead of industry trends by evaluating and adopting emerging data engineering tools, frameworks, and methodologies. Proactively propose and implement improvements that enhance data quality, performance, and scalability.

Qualifications and Experience

To excel in this role, you will bring a blend of technical proficiency, strategic thinking, and leadership experience. We are looking for:

• Education: A bachelor’s or master’s degree in computer science, data science, information science, business administration, or a related field. Alternatively, equivalent work experience in data engineering or technology roles may be considered.
• Technical Expertise: Minimum 5 to 8 years of hands-on experience in data engineering, with a strong focus on ETL/ELT processes, data warehousing, and integration technologies. Proficiency in tools such as Microsoft SSIS, Talend, Informatica, and SQL (including advanced DML and dimensional modeling techniques) is essential. Experience with streaming platforms like Apache Spark, Kafka, and ksqlDB is a significant advantage.
• Industry-Specific Knowledge: 3 to 5 years of experience within the banking and financial services sector, where you have gained insights into the unique challenges and requirements of financial data systems. Your understanding of banking products, regulatory compliance, and financial data analytics will be invaluable.
• Leadership and Collaboration: Proven ability to lead technical projects, mentor junior engineers, and collaborate effectively with cross-functional teams. Your communication skills should enable you to articulate technical concepts clearly to both technical and non-technical stakeholders, fostering trust and alignment.
• Organizational and Analytical Skills: Exceptional organizational skills to manage complex projects, assimilate large volumes of data, and drive data-driven decision-making. Your analytical mindset will enable you to identify inefficiencies, propose optimizations, and implement solutions that deliver measurable business impact.

If you are a detail-oriented, innovative leader with a passion for data engineering and a commitment to driving organizational success through robust data infrastructure, we invite you to join our team. Together, we will shape the future of data in banking and technology, empowering our organization to thrive in an increasingly data-centric world.