Architect Advanced
Mphasis, Dallas, TX, United States
Role Description
Senior Level Data Architect with data analytics experience, Databricks, Pyspark, Python, ETL tools like Informatica.
Job Summary
Senior Level Data Architect with data analytics experience, Databricks, Pyspark, Python, ETL tools like Informatica.
This is a key role that requires senior/lead with great communication skills who is very proactive with risk & issue management.
Experience and Education Required
15+ years of experience as Data Analyst / Data Engineer with Databricks on AWS expertise in designing and implementing scalable, secure, and cost-effic eent data solutions on AWS.
Job Profile
Hands‑on data analytics experience with Databricks on AWS, Pyspark and Python.
Prior experience migrating a data asset to the cloud using a GenAI automation option.
Experience migrating data from on-premises to AWS.
Expertise in developing data models, delivering data-driven insights for business solutions.
Experience in pretraining, fine‑tuning, augmenting and optimizing large language models (LLMs).
Designing and implementing database solutions, developing PySpark applications to extract, transform, and aggregate data, generating insights.
Data Collection & Integration: Identify, gather, and consolidate data from diverse sources, including internal databases and spreadsheets ensuring data integrity and relevance.
Data Cleaning & Transformation: Apply thorough data quality checks, cleaning processes, and transformations using Python (Pandas) and SQL to prepare datasets.
Automation & Scalability: Develop and maintain scripts that automate repetitive data preparation tasks.
Autonomy & Proactivity: Operate with minimal supervision, demonstrating initiative in problem‑solving, prioritizing tasks, and continuously improving the quality and impact of your work.
Technical Skills
15+ years of experience as a Data Analyst, Data Engineer, or related role, ideally with a bachelor’s degree or higher in a relevant field.
Strong proficiency in Python (Pandas, Scikit-learn, Matplotlib) and SQL, with experience working across various data formats and sources.
Proven ability to automate data workflows, implement code‑based best practices, and maintain documentation to ensure reproducibility and scalability.
Behavioral Skills
Ability to manage in tight circumstances, very proactive with risk & issue management.
Requirement Clarification & Communication: Interact directly with colleagues to clarify objectives, challenge assumptions.
Documentation & Best Practices: Maintain clear, concise documentation of data workflows, coding standards, and analytical methodologies to support knowledge transfer and scalability.
Collaboration & Stakeholder Engagement: Work closely with colleagues who provide data, raising questions about data validity, sharing insights, and co‑creating solutions that address evolving needs.
Excellent communication skills for engaging with colleagues, clarifying requirements, and conveying analytical results in a meaningful, non‑technical manner.
Demonstrated critical thinking skills, including the willingness to question assumptions, evaluate data quality, and recommend alternative approaches when necessary.
A self‑directed, resourceful problem‑solver who collaborates well with others while confidently managing tasks and priorities independently.
Salary
Salary range: $100,000 to $173,500.
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Senior Level Data Architect with data analytics experience, Databricks, Pyspark, Python, ETL tools like Informatica.
Job Summary
Senior Level Data Architect with data analytics experience, Databricks, Pyspark, Python, ETL tools like Informatica.
This is a key role that requires senior/lead with great communication skills who is very proactive with risk & issue management.
Experience and Education Required
15+ years of experience as Data Analyst / Data Engineer with Databricks on AWS expertise in designing and implementing scalable, secure, and cost-effic eent data solutions on AWS.
Job Profile
Hands‑on data analytics experience with Databricks on AWS, Pyspark and Python.
Prior experience migrating a data asset to the cloud using a GenAI automation option.
Experience migrating data from on-premises to AWS.
Expertise in developing data models, delivering data-driven insights for business solutions.
Experience in pretraining, fine‑tuning, augmenting and optimizing large language models (LLMs).
Designing and implementing database solutions, developing PySpark applications to extract, transform, and aggregate data, generating insights.
Data Collection & Integration: Identify, gather, and consolidate data from diverse sources, including internal databases and spreadsheets ensuring data integrity and relevance.
Data Cleaning & Transformation: Apply thorough data quality checks, cleaning processes, and transformations using Python (Pandas) and SQL to prepare datasets.
Automation & Scalability: Develop and maintain scripts that automate repetitive data preparation tasks.
Autonomy & Proactivity: Operate with minimal supervision, demonstrating initiative in problem‑solving, prioritizing tasks, and continuously improving the quality and impact of your work.
Technical Skills
15+ years of experience as a Data Analyst, Data Engineer, or related role, ideally with a bachelor’s degree or higher in a relevant field.
Strong proficiency in Python (Pandas, Scikit-learn, Matplotlib) and SQL, with experience working across various data formats and sources.
Proven ability to automate data workflows, implement code‑based best practices, and maintain documentation to ensure reproducibility and scalability.
Behavioral Skills
Ability to manage in tight circumstances, very proactive with risk & issue management.
Requirement Clarification & Communication: Interact directly with colleagues to clarify objectives, challenge assumptions.
Documentation & Best Practices: Maintain clear, concise documentation of data workflows, coding standards, and analytical methodologies to support knowledge transfer and scalability.
Collaboration & Stakeholder Engagement: Work closely with colleagues who provide data, raising questions about data validity, sharing insights, and co‑creating solutions that address evolving needs.
Excellent communication skills for engaging with colleagues, clarifying requirements, and conveying analytical results in a meaningful, non‑technical manner.
Demonstrated critical thinking skills, including the willingness to question assumptions, evaluate data quality, and recommend alternative approaches when necessary.
A self‑directed, resourceful problem‑solver who collaborates well with others while confidently managing tasks and priorities independently.
Salary
Salary range: $100,000 to $173,500.
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