Estrada Consulting Incorporated
Lead Developer - Data / BI & GenAI (Ref: 5788)
Sacramento, California•Contract
About the Job
Position: Lead Developer – Data, Business Intelligence & Generative AI (Ref: 5788)
Location: Onsite in Sacramento, CA is mandatory
Duration: 12-36 months
Rate: DOE
References: Three previous client references will be required.
Education: Degree PDF copy is required. If no Degree then it is allowable for four years additional experience in lieu of the degree copy.
Position Overview
We are seeking an experienced Lead Developer – Data, Business Intelligence & Generative AI to provide technical leadership and hands-on development for an enterprise Investment Data Warehouse (IDW) and advanced analytics environment.
The Lead Developer will lead the design, development, enhancement, deployment, and ongoing support of enterprise-level Business Intelligence (BI), Generative BI (GenBI), Artificial Intelligence/Machine Learning (AI/ML), and Generative AI (GenAI) solutions. The role will focus on accelerating the delivery of investment-related analytics, predictive capabilities, natural-language data interaction, and agentic AI solutions within AWS and Snowflake ecosystems.
This is a senior hands-on technical leadership position requiring deep expertise across data engineering, BI, cloud data platforms, AI/ML, large language models (LLMs), advanced SQL, data modeling, and modern full-stack development.
The Lead Developer will lead and mentor technical team members while collaborating directly with business stakeholders, analysts, developers, third-party vendors, and technical support teams to translate complex business requirements into secure, scalable, production-grade data and AI solutions.
Key Responsibilities
The Lead Developer will:
Location: Onsite in Sacramento, CA is mandatory
Duration: 12-36 months
Rate: DOE
References: Three previous client references will be required.
Education: Degree PDF copy is required. If no Degree then it is allowable for four years additional experience in lieu of the degree copy.
Position Overview
We are seeking an experienced Lead Developer – Data, Business Intelligence & Generative AI to provide technical leadership and hands-on development for an enterprise Investment Data Warehouse (IDW) and advanced analytics environment.
The Lead Developer will lead the design, development, enhancement, deployment, and ongoing support of enterprise-level Business Intelligence (BI), Generative BI (GenBI), Artificial Intelligence/Machine Learning (AI/ML), and Generative AI (GenAI) solutions. The role will focus on accelerating the delivery of investment-related analytics, predictive capabilities, natural-language data interaction, and agentic AI solutions within AWS and Snowflake ecosystems.
This is a senior hands-on technical leadership position requiring deep expertise across data engineering, BI, cloud data platforms, AI/ML, large language models (LLMs), advanced SQL, data modeling, and modern full-stack development.
The Lead Developer will lead and mentor technical team members while collaborating directly with business stakeholders, analysts, developers, third-party vendors, and technical support teams to translate complex business requirements into secure, scalable, production-grade data and AI solutions.
Key Responsibilities
The Lead Developer will:
- Provide technical leadership and solution guidance to developers and analysts responsible for enterprise BI, data warehouse, GenBI, GenAI, and AI/ML solutions.
- Lead teams through requirements discovery, architecture, design, development, testing, deployment, maintenance, and continuous improvement of enterprise data products.
- Design, develop, enhance, and support enterprise data warehouse and analytics solutions within AWS, Snowflake, and related cloud ecosystems.
- Build and maintain production-grade BI and data products, including analytics dashboards, dimensional and semantic data models, APIs, reports, and interactive analytics applications.
- Design and develop ETL/ELT pipelines and data integration, cleansing, transformation, and orchestration processes using technologies such as Airflow, dbt, Matillion, and comparable platforms.
- Develop and optimize solutions using cloud data warehouses and data platforms such as Snowflake, Amazon Redshift, BigQuery, and Azure Synapse.
- Apply advanced SQL, including complex joins, window functions, query optimization, troubleshooting, and performance tuning.
- Design enterprise data models utilizing star schemas, snowflake schemas, dimensional modeling, and semantic layers.
- Develop analytics and reporting solutions using major BI platforms such as Power BI, Tableau, and Looker.
- Design and implement natural-language-to-SQL/query solutions that enable users to securely obtain business insights through conversational interfaces.
- Utilize OpenAI APIs and comparable LLM platforms to develop GenAI-enabled analytics and business intelligence capabilities.
- Perform continuous prompt engineering, including designing and refining prompt strategies that guide system behavior and improve the reliability and usefulness of generated business insights.
- Develop automated testing and validation processes for Text-to-SQL and GenAI solutions, including safeguards designed to identify hallucinations, incorrect calculations, and unreliable outputs.
- Leverage platform-native AI capabilities and APIs, including technologies such as Snowflake Cortex and AWS Bedrock, to accelerate development of GenAI and analytics use cases.
- Design and prototype AI/ML solutions involving statistical analysis, predictive analytics, optimization, and machine learning, using frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Support the development of agentic AI workflows and orchestration, Generative AI design patterns, and AI-enabled enterprise applications.
- Design intuitive analytics interfaces and dashboards using UI/UX and human-centered design principles and technologies such as Chainlit, Streamlit, and React.
- Create interactive reports, visualizations, and data storytelling solutions based on established data visualization best practices.
- Implement and support Docker and Kubernetes containerization and orchestration.
- Operate and enhance CI/CD pipelines supporting data, AI/ML, and analytics workflows.
- Monitor, troubleshoot, tune, and maintain AI/ML solutions, GenBI applications, ETL/ELT pipelines, data warehouses, data lakes, and related cloud services.
- Apply infrastructure automation technologies such as Terraform and Ansible where appropriate.
- Ensure data and AI solutions are designed and maintained to be secure, scalable, reliable, supportable, and cost-effective.
- Apply expertise in cloud strategy, FinOps, security, compliance, and AI governance to enterprise data and AI initiatives.
- Analyze emerging technologies, solution vendors, and market trends and assess their potential impact and value to the organization's data and analytics environment.
- Develop technical presentations, architecture diagrams, models, recommendations, design documentation, and other technical artifacts.
- Serve as a technical liaison between business stakeholders, developers, analysts, technical support personnel, and third-party vendors.
- Provide ongoing knowledge transfer, mentoring, documentation, and technical guidance to internal staff.
- Support maintenance and operations of deployed data, BI, GenBI, and AI/ML solutions in addition to new development.
Minimum Qualifications
Candidates must possess:
Candidates must possess:
- Ten (10) or more years of experience in data engineering, business intelligence engineering, and/or analytics.
- Five (5) or more years of experience leading a team of at least three members implementing enterprise-level BI and/or large data warehouse solutions.
- Five (5) or more years of experience working with AI/ML and/or Generative AI technologies.
- Experience successfully delivering at least two production-grade BI or data products, such as dashboards, data models, APIs, or comparable enterprise solutions.
- Two (2) or more years of experience with ETL/ELT pipelines, data warehousing platforms such as Snowflake or Amazon Redshift, and orchestration/transformation technologies such as Airflow, dbt, or comparable tools.
- Two (2) or more years of experience using OpenAI APIs or comparable LLM platforms, including:
- Developing natural-language-to-SQL/query systems;
- Designing prompt strategies for business intelligence, analytics, and business insights; and
- Performing prompt engineering to guide and refine platform/system behavior.
- Two (2) or more years of experience with:
- Advanced SQL, including advanced joins, window functions, and performance tuning;
- Data modeling, including star/snowflake schemas and semantic layers; and
- At least one major BI platform, such as Power BI, Tableau, or Looker.
- Two (2) or more years of experience leading analysts and developers and collaborating with business and technical stakeholders to discover, document, translate, and implement requirements and stakeholder requests for data warehouse and/or business intelligence projects.
Highly Desired Qualifications
Preference will be given to candidates possessing one or more relevant technical certifications or credentials, including:
Preference will be given to candidates possessing one or more relevant technical certifications or credentials, including:
- AWS certifications
- Snowflake certifications
- Microsoft Power BI certifications
- Tableau certifications
- AI/ML or Generative AI coursework, certifications, or professional credentials
A Bachelor's degree in Computer Science, Computer Engineering, or a related field from an accredited or government-sanctioned college or university is highly desired. Candidates should be prepared to provide documentation of their degree if requested.
Technical Environment
The ideal candidate will bring hands-on experience across several of the following technologies:
Data & BI: Snowflake, Amazon Redshift, BigQuery, Azure Synapse, Power BI, Tableau, Looker, dbt, Airflow, Matillion, advanced SQL, dimensional modeling, star/snowflake schemas, semantic layers.
AI/ML & GenAI: OpenAI APIs, LLM platforms, Snowflake Cortex, AWS Bedrock, natural-language-to-SQL/Text-to-SQL, prompt engineering, agentic AI, TensorFlow, PyTorch, scikit-learn, predictive analytics and machine learning.
Application & UI: React, Streamlit, Chainlit, APIs, interactive dashboards, data visualization, UI/UX and human-centered design.
Cloud & DevOps: AWS, Docker, Kubernetes, CI/CD, Terraform, Ansible, cloud infrastructure automation, monitoring, logging, security, AI governance and FinOps.
Work Location & Schedule
This position follows a hybrid work model in West Sacramento, California, requiring the selected resource to work on-site two (2) to three (3) business days per week.
The work arrangement may change based on organizational business needs and could include increased on-site work, remote work, or adjusted work hours. Work schedules are subject to management approval and applicable organizational policies and procedures.
The selected resource must generally be available during established business hours. Travel and commuting expenses associated with fulfilling the on-site requirement are the responsibility of the selected resource.
Ideal Candidate
The ideal candidate is not solely a BI developer or data engineer. This role requires a senior technical lead who can bridge enterprise data engineering, BI, cloud architecture, AI/ML, and Generative AI while remaining hands-on with solution delivery.
The strongest candidate will have demonstrated experience taking complex data and AI initiatives from requirements and architecture through production deployment and ongoing support, while successfully leading technical teams and communicating with both technical and business stakeholders.
Technical Environment
The ideal candidate will bring hands-on experience across several of the following technologies:
Data & BI: Snowflake, Amazon Redshift, BigQuery, Azure Synapse, Power BI, Tableau, Looker, dbt, Airflow, Matillion, advanced SQL, dimensional modeling, star/snowflake schemas, semantic layers.
AI/ML & GenAI: OpenAI APIs, LLM platforms, Snowflake Cortex, AWS Bedrock, natural-language-to-SQL/Text-to-SQL, prompt engineering, agentic AI, TensorFlow, PyTorch, scikit-learn, predictive analytics and machine learning.
Application & UI: React, Streamlit, Chainlit, APIs, interactive dashboards, data visualization, UI/UX and human-centered design.
Cloud & DevOps: AWS, Docker, Kubernetes, CI/CD, Terraform, Ansible, cloud infrastructure automation, monitoring, logging, security, AI governance and FinOps.
Work Location & Schedule
This position follows a hybrid work model in West Sacramento, California, requiring the selected resource to work on-site two (2) to three (3) business days per week.
The work arrangement may change based on organizational business needs and could include increased on-site work, remote work, or adjusted work hours. Work schedules are subject to management approval and applicable organizational policies and procedures.
The selected resource must generally be available during established business hours. Travel and commuting expenses associated with fulfilling the on-site requirement are the responsibility of the selected resource.
Ideal Candidate
The ideal candidate is not solely a BI developer or data engineer. This role requires a senior technical lead who can bridge enterprise data engineering, BI, cloud architecture, AI/ML, and Generative AI while remaining hands-on with solution delivery.
The strongest candidate will have demonstrated experience taking complex data and AI initiatives from requirements and architecture through production deployment and ongoing support, while successfully leading technical teams and communicating with both technical and business stakeholders.