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Company Overview
This global technology consultancy partners with organizations to accelerate their transformation journeys through cloud-native solutions and modern engineering practices. The firm stands out for its belief that innovation should empower and not constrain clients’ independence. They blend technical depth with creativity, delivering pragmatic, human-centered solutions that enable businesses to evolve with confidence. Known for its straightforward yet groundbreaking approach, the company is helping public and private sector clients modernize data infrastructure and unlock measurable impact. Role Summary
The Lead Data Engineer will play a central role in shaping large-scale data transformation initiatives for the public sector. This position is ideal for a technically accomplished leader who thrives at the intersection of data strategy, engineering excellence, and cloud innovation. The role involves leading a high-performing data engineering team, architecting enterprise-grade data solutions, and ensuring the delivery of secure, scalable, and cost-effective platforms leveraging AWS technologies. Key Responsibilities
Oversee and strategize data engineering function, ensuring delivery excellence and professional growth. Design and implement scalable data pipelines and data platforms using AWS services. Define and enforce data engineering best practices, governance, and security frameworks. Collaborate with business stakeholders to translate complex requirements into actionable data solutions. Optimize data workflows and infrastructure for performance, scalability, and cost efficiency. Oversee data modeling, ETL/ELT development, and the implementation of data quality frameworks. Serve as a trusted technical advisor, presenting data solutions to both technical and non-technical audiences. Core Requirements
7+ years of experience in data engineering with 3+ years specializing in AWS data stack (Glue, Redshift, S3, EMR, Lambda, Athena). Experienced in SQL and at least one major programming language (Python, Scala, or Java). Overseen the designing and implementation of enterprise data lake and data warehouse architectures. Well-verse with data governance, medallion architecture, and performance optimization. Used orchestration tools such as Airflow or Step Functions. Strong leadership, communication, and stakeholder management capabilities. Preferred Experience
Familiarity with Databricks, Delta Lake, and BI tools such as Power BI, Tableau, or Qlik Sense. Experience developing semantic layers and self-service analytics models. Exposure to real-time data processing frameworks. Relevant AWS certifications (e.g., Data Analytics or Solutions Architect).
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This global technology consultancy partners with organizations to accelerate their transformation journeys through cloud-native solutions and modern engineering practices. The firm stands out for its belief that innovation should empower and not constrain clients’ independence. They blend technical depth with creativity, delivering pragmatic, human-centered solutions that enable businesses to evolve with confidence. Known for its straightforward yet groundbreaking approach, the company is helping public and private sector clients modernize data infrastructure and unlock measurable impact. Role Summary
The Lead Data Engineer will play a central role in shaping large-scale data transformation initiatives for the public sector. This position is ideal for a technically accomplished leader who thrives at the intersection of data strategy, engineering excellence, and cloud innovation. The role involves leading a high-performing data engineering team, architecting enterprise-grade data solutions, and ensuring the delivery of secure, scalable, and cost-effective platforms leveraging AWS technologies. Key Responsibilities
Oversee and strategize data engineering function, ensuring delivery excellence and professional growth. Design and implement scalable data pipelines and data platforms using AWS services. Define and enforce data engineering best practices, governance, and security frameworks. Collaborate with business stakeholders to translate complex requirements into actionable data solutions. Optimize data workflows and infrastructure for performance, scalability, and cost efficiency. Oversee data modeling, ETL/ELT development, and the implementation of data quality frameworks. Serve as a trusted technical advisor, presenting data solutions to both technical and non-technical audiences. Core Requirements
7+ years of experience in data engineering with 3+ years specializing in AWS data stack (Glue, Redshift, S3, EMR, Lambda, Athena). Experienced in SQL and at least one major programming language (Python, Scala, or Java). Overseen the designing and implementation of enterprise data lake and data warehouse architectures. Well-verse with data governance, medallion architecture, and performance optimization. Used orchestration tools such as Airflow or Step Functions. Strong leadership, communication, and stakeholder management capabilities. Preferred Experience
Familiarity with Databricks, Delta Lake, and BI tools such as Power BI, Tableau, or Qlik Sense. Experience developing semantic layers and self-service analytics models. Exposure to real-time data processing frameworks. Relevant AWS certifications (e.g., Data Analytics or Solutions Architect).
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