Diligente Technologies

Compensation

Full Description

Lead Data Engineer – Technology | Data Platform Location: Remote / Dallas, TX Employment Type: Full-Time (Benefits Eligible) Compensation: $150K Base + 15% Bonus Client is seeking a Lead Data Engineer to architect, scale, and evolve a modern enterprise data platform supporting retail and consumer brands. This is a high-impact leadership role combining deep hands-on engineering expertise with architectural ownership and cross-functional influence. Role Overview The Lead Data Engineer will own the end-to-end design and delivery of scalable, secure, and cost-efficient data solutions built on AWS and cloud data warehouse technologies. The role requires strong technical depth in distributed data processing and cloud-native tooling, along with the ability to define engineering standards, mentor teams, and translate business requirements into measurable outcomes. This individual will drive platform evolution, enforce governance and quality frameworks, and lead cross-team initiatives to enable advanced analytics and AI-driven solutions. Must-Have Technical Expertise Candidates must demonstrate strong, hands-on experience in: • Python and/or PySpark • Apache Spark or similar distributed data processing frameworks • Cloud data warehouses such as Snowflake and/or Redshift • AWS ecosystem, including S3, EC2, EMR, Glue, Athena, Lambda, and CloudWatch • Strong SQL and advanced data modeling • Modern data tooling: • Apache Airflow • DBT • GitLab & CI/CD pipelines • Docker & Kubernetes • Designing scalable data pipelines and enterprise-grade architecture patterns • Implementing governance, data quality, metadata management, and compliance standards Leadership & Strategic Expectations (Critical for Success) This is not an individual contributor-only role. The ideal candidate must demonstrate: • Proven experience in a Lead or Architect capacity • Ability to define technical strategy and influence engineering standards across teams • Strong mentorship capability with structured coaching examples • Clear stakeholder management experience across product, analytics, and business functions • Ability to articulate measurable business impact and success metrics • Strong documentation practices aligned with governance and compliance requirements • Ownership of design reviews, code reviews, and process maturity Preferred Qualifications • Master’s degree in a related technical field • Experience with Apache Kafka or streaming platforms • Data governance tooling (e.g., Great Expectations, DataHub) • Experience in retail, e-commerce, or high-volume consumer environments • Cloud cost optimization expertise • Experience integrating AI-driven capabilities into data platforms Important Candidate Fit Criteria (Based on Prior Interview Feedback) To succeed in this role, candidates must clearly demonstrate: • Impact Articulation – Ability to quantify business value, performance improvements, cost savings, or scalability gains from past initiatives. • Depth of Mentorship – Concrete examples of structured mentorship, coaching frameworks, and measurable team growth outcomes. • Documentation & Governance Mindset – Strong commitment to documentation, data lineage, governance frameworks, and compliance standards. • Strategic Leadership – Evidence of leading platform evolution, defining architecture standards, and influencing cross-team processes—not just delivering technical tasks. • Stakeholder Management – Experience partnering with business and product teams to translate requirements into scalable technical solutions. Candidates who primarily demonstrate strong technical skills but lack leadership depth, governance orientation, stakeholder engagement, or strategic platform ownership may not be the right fit for this Lead-level opportunity.