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.
Apply for this job in 1 click
Skip the repetitive application forms
Install the Base Career Chrome Extension and autofill job applications across major job boards with your profile.
Trusted by over 500,000 job seekers on Base Career
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.
About CG Infinity
IT Services & Consulting542 employeesFounded 1998
Private technology consulting firm helping energy, utilities, and financial-services companies with data, AI, cloud, and Salesforce.
