Senior Data Engineer at HP Law

Spring, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

21 Jan, 26

Salary

0.0

Posted On

23 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Databricks, Apache Spark, AWS, Azure, ETL, Data Integration, Data Modeling, Power BI, Tableau, A/B Testing, Statistical Analysis, MLOps, Agile, CI/CD

Industry

IT Services and IT Consulting

Description

Design, build, and maintain scalable ETL pipelines to process and analyze large datasets across millions of devices. Develop and optimize data integration workflows, enabling enriched device-level metadata for targeted marketing campaigns. Work with structured and unstructured data, implementing data modeling, transformation, and preprocessing techniques. Leverage Python, SQL, Databricks, and Apache Spark for data exploration, mining, cleansing, and transformation. Develop and maintain big data solutions on cloud platforms like AWS and Azure (e.g., COSMOS DB, Redshift, Athena). Conduct A/B testing, statistical analysis, and hypothesis testing to improve user engagement and business KPIs. Build and optimize dashboards and visualizations using Power BI, Tableau, and other business intelligence tools. Collaborate with data scientists, analysts, and business stakeholders to translate data insights into strategic actions. Follow Agile development methodologies and leverage CI/CD pipelines, version control (Git), and test automation. Knowledge of secure coding practices, Strong understanding of cybersecurity principles, frameworks, and best practices. Solid understanding of supervised, unsupervised, and reinforcement learning techniques. Build and deploy ML models into production systems with robust MLOps practices Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, Statistics/ Mathematics, or any other related discipline or commensurate work experience or demonstrated competence. Experience: 7-10 years of work experience, preferably in data analytics, data engineering, data modeling, or a related field. Programming: Proficiency in Python and SQL Big Data & Cloud: Hands-on experience with Databricks, Apache Spark, AWS (Redshift, Athena), and Azure (COSMOS DB). Data Processing: Strong skills in ETL pipelines, data integration, and transformation of large datasets. Analytics & Visualization: Experience with Power BI, Tableau, and Adobe Analytics for reporting and insights. Testing & Optimization: Knowledge of A/B testing, statistical analysis, and hypothesis testing to improve business outcomes. Proficiency in API development & integration (Restful APIs, GraphQL, Postman), ability to understand third-party API documentation Software Engineering Best Practices: Experience with Git, CI/CD, Agile methodologies, and automated testing.

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Responsibilities

Design, build, and maintain scalable ETL pipelines to process and analyze large datasets. Collaborate with data scientists, analysts, and business stakeholders to translate data insights into strategic actions.