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Our people-first approach to technology offers best-in-class service and success rates.
The Role
Leads the architecture, engineering, and delivery of enterprise data platforms and analytics solutions for clients. Advises executive and technical stakeholders, facilitates discovery and architecture sessions, designs cloud-based batch and streaming systems, and remains hands-on with pipelines, code reviews, proofs of concept, and complex technical issues. Establishes DataOps, governance, security, and engineering standards; mentors data teams; leads distributed delivery teams; and supports estimation, proposals, presentations, and pre-sales activities.
Summary Generated by Built In
We are seeking a Principal Data Engineer to lead the architecture, design, and delivery of modern data platforms and analytics solutions for clients. This is a hands-on technical leadership role for someone who can move comfortably between executive-level client conversations, solution architecture, engineering delivery, and mentoring high-performing data teams.
The ideal candidate combines deep data-engineering expertise with strong consulting instincts: they can translate business objectives into scalable technical solutions, communicate complex concepts through clear presentations, and guide teams from discovery through implementation and operationalization.
Key Responsibilities
The ideal candidate combines deep data-engineering expertise with strong consulting instincts: they can translate business objectives into scalable technical solutions, communicate complex concepts through clear presentations, and guide teams from discovery through implementation and operationalization.
Key Responsibilities
- Lead the end-to-end architecture, design, and delivery of enterprise data engineering, data platform, and analytics solutions for client engagements.
- Serve as a trusted technical advisor to client stakeholders, including technology leaders, data leaders, architects, and business partners.
- Facilitate discovery sessions, requirements workshops, technical assessments, architecture reviews, and solution-design discussions.
- Translate business goals, data challenges, and operating-model requirements into practical data strategies, roadmaps, reference architectures, and implementation plans.
- Define scalable, secure, reliable, and cost-effective architectures for data ingestion, transformation, storage, governance, orchestration, analytics, and data consumption.
- Remain hands-on in engineering work, including designing data pipelines, reviewing code, building proof of concepts, resolving complex technical issues, and establishing engineering patterns.
- Architect and implement batch, real-time, streaming, and event-driven data solutions as appropriate for client needs.
- Design modern cloud data platforms using technologies such as Snowflake, Databricks, Microsoft Fabric, Azure Data Factory, AWS Glue, Amazon Redshift, BigQuery, or equivalent platforms.
- Lead the development of robust ETL/ELT pipelines, data models, data APIs, semantic layers, and data products.
- Establish data engineering standards for code quality, testing, CI/CD, observability, metadata management, data lineage, documentation, security, and production support.
- Drive adoption of DataOps practices, infrastructure as code, automated testing, deployment pipelines, monitoring, and incident-management processes.
- Partner with data architects, data scientists, analysts, application architects, security teams, and business stakeholders to ensure solutions are aligned to enterprise architecture and business outcomes.
- Present technical recommendations, architecture options, delivery status, risks, and strategic roadmaps to both technical and executive audiences.
- Lead client-facing demonstrations, workshops, steering-committee updates, and technical presentations.
- Mentor senior, mid-level, and junior data engineers; provide technical coaching, career guidance, design feedback, and hands-on support.
- Lead and influence cross-functional delivery teams, including onshore/offshore engineers, architects, analysts, and client technical resources.
- Participate in project estimation, staffing, delivery planning, risk management, solution scoping, and proposal development.
- Support pre-sales and business-development activities, including solutioning, client presentations, technical discovery, RFP responses, estimates, and statement-of-work development.
- Stay current on emerging data, cloud, AI, governance, and analytics technologies; evaluate where they provide meaningful business value for clients.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field; equivalent professional experience may be considered.
- 10+ years of progressive experience in data engineering, data warehousing, data integration, data architecture, or related technical disciplines.
- 3+ years of experience in a technical leadership, lead engineer, solution architect, staff engineer, principal engineer, or consulting leadership capacity.
- Demonstrated experience architecting and delivering enterprise-scale data platforms and data integration solutions.
- Strong hands-on expertise in SQL and at least one modern programming language, preferably Python, Scala, Java, or C#.
- Strong experience with ETL/ELT design, data pipeline development, data transformation frameworks, orchestration, and workflow automation.
- Experience with one or more cloud providers: Microsoft Azure, AWS, or Google Cloud Platform.
- Experience with modern cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, BigQuery, Redshift, or similar technologies.
- Experience with orchestration and pipeline technologies such as Apache Airflow, Azure Data Factory, AWS Step Functions, dbt, Dagster, Prefect, or equivalent tools.
- Knowledge of distributed data-processing technologies such as Apache Spark, Kafka, Flink, Hadoop ecosystems, or comparable platforms.
- Experience designing both batch and near-real-time or streaming data solutions.
- Strong understanding of dimensional modeling, data vault, normalized data models, lakehouse architectures, data lake architectures, and data warehouse design principles.
- Experience implementing data quality, data validation, monitoring, lineage, metadata, governance, and security controls.
- Working knowledge of DevOps and DataOps practices, including Git-based source control, CI/CD, automated testing, deployment automation, and infrastructure as code.
- Strong understanding of cloud security principles, identity and access management, encryption, secrets management, and role-based access controls.
- Proven ability to lead architecture discussions and make well-reasoned technical tradeoffs involving performance, scalability, reliability, maintainability, security, and cost.
- Excellent verbal, written, and presentation skills, with the ability to explain technical concepts clearly to business stakeholders and executive audiences.
- Experience in a consulting, professional services, systems integrator, or client-facing delivery environment.
- Experience designing data platforms that support AI, machine learning, generative AI, retrieval-augmented generation, feature stores, vector databases, or advanced analytics workloads.
- Certifications in AWS, Azure, Google Cloud, Databricks, Snowflake, Microsoft Fabric, or other relevant data technologies.
- Experience with master data management, data cataloging, data governance, privacy, regulatory compliance, or data stewardship programs.
- Experience with tools such as Collibra, Alation, Microsoft Purview, Unity Catalog, Informatica, Monte Carlo, Great Expectations, or similar governance and observability platforms.
- Experience with Salesforce, SAP, ERP, CRM, finance, supply-chain, healthcare, retail, manufacturing, or other enterprise operational data domains.
- Familiarity with BI and semantic-layer technologies such as Power BI, Tableau, Looker, ThoughtSpot, or similar platforms.
- Experience with containerization and cloud-native technologies such as Docker, Kubernetes, Terraform, CloudFormation, Bicep, or Pulumi.
- Prior experience contributing to proposals, estimates, statements of work, or technical sales pursuits.
- Experience managing or leading distributed onshore/offshore delivery teams.
Skills Required
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent professional experience
- 10+ years of progressive experience in data engineering, data warehousing, data integration, data architecture, or related technical disciplines
- 3+ years in a technical leadership, lead engineer, solution architect, staff engineer, principal engineer, or consulting leadership capacity
- Experience architecting and delivering enterprise-scale data platforms and data integration solutions
- Strong hands-on SQL expertise and proficiency in at least one modern programming language, preferably Python, Scala, Java, or C#
- Experience with ETL/ELT design, data pipelines, data transformation frameworks, orchestration, and workflow automation
- Experience with Microsoft Azure, AWS, or Google Cloud Platform
- Experience with modern cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, BigQuery, or Redshift
- Experience with Apache Airflow, Azure Data Factory, AWS Step Functions, dbt, Dagster, Prefect, or equivalent orchestration tools
- Knowledge of Apache Spark, Kafka, Flink, Hadoop ecosystems, or comparable distributed data-processing technologies
- Experience designing batch and near-real-time or streaming data solutions
- Understanding of dimensional modeling, data vault, normalized data models, lakehouse architectures, data lake architectures, and data warehouse design
- Experience implementing data quality, validation, monitoring, lineage, metadata, governance, and security controls
- Working knowledge of DevOps and DataOps, Git-based source control, CI/CD, automated testing, deployment automation, and infrastructure as code
- Understanding of cloud security, identity and access management, encryption, secrets management, and role-based access controls
- Ability to lead architecture discussions and make technical tradeoffs involving performance, scalability, reliability, maintainability, security, and cost
- Excellent verbal, written, and presentation skills for technical, business, and executive audiences
- Experience in consulting, professional services, systems integration, or client-facing delivery
- Experience designing data platforms for AI, machine learning, generative AI, retrieval-augmented generation, feature stores, vector databases, or advanced analytics
- Certifications in AWS, Azure, Google Cloud, Databricks, Snowflake, Microsoft Fabric, or relevant data technologies
- Experience with master data management, data cataloging, governance, privacy, regulatory compliance, or data stewardship
- Experience with Collibra, Alation, Microsoft Purview, Unity Catalog, Informatica, Monte Carlo, Great Expectations, or similar tools
- Experience with Salesforce, SAP, ERP, CRM, finance, supply chain, healthcare, retail, or manufacturing data domains
- Familiarity with Power BI, Tableau, Looker, ThoughtSpot, or similar BI and semantic-layer technologies
- Experience with Docker, Kubernetes, Terraform, CloudFormation, Bicep, or Pulumi
- Experience contributing to proposals, estimates, statements of work, or technical sales pursuits
- Experience managing or leading distributed onshore/offshore delivery teams
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The Company
What We Do
Our people-first approach to technology offers best-in-class service and success rates. With the world of business and technology growing more complex and confusing every minute, CG Infinity keeps it simple for our clients. Your leaders work with our leaders throughout an engagement. The leaders of our small, blended teams work hand in hand with your team to ensure your objective success. We partner with companies in a vast array of industries, including the Energy & Utilities and Financial Services industries, to help them thrive in the modern marketplace by leveraging technology to drive their enterprise. From our perfect record in Salesforce implementations, our trusted experience integrating Salesforce with back-end applications, to our creative custom software solutions, CG Infinity is your trusted ally for business technology transitions. With our skilled employees and veteran leadership team, CG Infinity doesn’t complicate life for our clients, we simplify.
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