Lead Data Engineer

Job Summary

We are looking for an experienced Lead Data Engineer with pre-sales experience to lead the design, development, and implementation of scalable data engineering solutions while supporting business development and client engagements.

The ideal candidate will possess strong technical expertise in data architecture, data integration, cloud data platforms, ETL/ELT pipelines, and modern analytics technologies, combined with the ability to understand client requirements, present technical solutions, conduct solution demonstrations, and contribute to pre-sales activities.

This role will work closely with sales, business development, solution architects, and delivery teams to translate business challenges into effective, scalable, and commercially viable data solutions.

Key Responsibilities

1. Data Engineering and Technical Leadership

• Lead the design, development, and implementation of scalable, reliable, and high-performance data pipelines and data platforms.

• Define data architecture, data integration strategies, data models, and engineering best practices.

• Oversee the development of ETL/ELT pipelines, data warehouses, data lakes, and lakehouse solutions.

• Ensure data quality, security, governance, performance, and operational reliability.

• Lead technical reviews, troubleshoot complex data engineering issues, and provide guidance to data engineers.

• Evaluate emerging data technologies and recommend solutions aligned with business and technical requirements.

2. Pre-Sales and Solution Consulting

• Collaborate with sales and business development teams to identify client needs and propose appropriate data engineering solutions.

• Participate in client discovery sessions, requirement-gathering workshops, and technical consultations.

• Translate business requirements into technical solution architectures, implementation approaches, and project scope.

• Prepare and deliver technical presentations, solution demonstrations, proof of concepts (POCs), and proposals.

• Provide technical estimates, resource requirements, implementation timelines, and high-level cost assessments.

• Explain complex technical concepts and solution benefits to both technical and non-technical stakeholders.

• Support sales pursuits by identifying opportunities for data modernization, cloud migration, analytics, and AI-ready data platforms.

3. Client Engagement and Stakeholder Management

• Build strong relationships with clients, understanding their business objectives, existing data environments, and technical challenges.

• Act as a trusted technical advisor throughout the pre-sales and solution design process.

• Work with delivery teams to ensure proposed solutions are technically feasible, commercially sound, and aligned with client expectations.

• Support the transition from pre-sales to project delivery, ensuring clear documentation of requirements, assumptions, and solution designs.

4. Project Delivery and Continuous Improvement

• Establish engineering standards, coding practices, documentation guidelines, and reusable solution components.

• Monitor project deliverables, technical risks, and solution quality.

• Identify opportunities to improve data processing efficiency, scalability, and cost optimization.

• Mentor team members and promote knowledge sharing across engineering and solution consulting teams.

Qualifications and Requirements

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related field.

• At least 5–8 years of experience in data engineering, data architecture, or related technical roles, with experience leading technical teams or projects.

• Proven experience in pre-sales, solution consulting, technical sales, or client-facing solution design.

• Strong knowledge of SQL, Python, data modeling, and database technologies.

• Hands-on experience designing and implementing ETL/ELT pipelines and large-scale data integration solutions.

• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.

• Familiarity with modern data platforms and technologies such as Snowflake, Databricks, BigQuery, Microsoft Fabric, Apache Spark, Kafka, or equivalent tools.

• Experience with data warehouses, data lakes, lakehouse architectures, and business intelligence integration.

• Ability to create solution architecture diagrams, technical proposals, project estimates, and proof-of-concept implementations.

• Excellent communication, presentation, analytical, and stakeholder management skills.

• Ability to manage multiple priorities and collaborate effectively across technical and commercial teams.

Preferred Qualifications

• Experience in consulting, systems integration, technology services, or enterprise solution delivery.

• Experience supporting enterprise sales cycles and responding to RFPs/RFIs.

• Knowledge of data governance, data security, master data management, and regulatory compliance.

• Familiarity with BI and analytics tools such as Power BI, Tableau, or Looker.

• Exposure to AI/ML data platforms, generative AI solutions, or enterprise data modernization initiatives.

• Relevant cloud or data platform certifications are an advantage.

Key Competencies

• Technical leadership and solution architecture

• Pre-sales consulting and solution positioning

• Client relationship management

• Business requirements analysis

• Technical presentation and proposal development

• Problem-solving and strategic thinking

• Team mentoring and cross-functional collaboration

What We Offer

• Opportunity to lead impactful data engineering and modernization initiatives.

• Exposure to enterprise clients and diverse technology environments.

• Career growth across technical leadership, solution architecture, and consulting.

• Collaborative environment working with sales, engineering, and delivery teams.

• Competitive compensation and benefits package.