SNR PRINCIPAL DATA ENGINEER

As a Principal Data Engineer, you will be at the forefront of Oracle’s data initiatives, playing a pivotal role in transforming raw data into actionable insights.
Collaborating with data scientists and business stakeholders, you will design scalable data pipelines, optimize data infrastructure, and ensure the availability of high-quality datasets for strategic analysis.
This role goes beyond data engineering, requiring hands-on involvement in statistical analysis and predictive modeling.
You will use techniques such as regression analysis, trend forecasting, and time-series modeling to extract meaningful insights from data, directly supporting business decision-making.
While advanced machine learning expertise is not required, a strong foundation in applied statistics and the ability to derive predictive insights are essential.
By bridging the gap between engineering and analytics, you will contribute to solutions that drive critical business outcomes.
Your work will ensure that data is not only reliable and accessible but also ready for interpretation and actionable use by data scientists and decision-makers.
This unique opportunity combines technical excellence with analytical impact, shaping the future of Oracle’s data-driven strategies.
areer Level - IC5 The senior data engineer’s responsibilities include.
Analyzing and interpreting complex datasets to generate insights that directly influence business strategy and decision-making.
You will applyadvanced statistical analysisandpredictive modelingtechniques to identify trends, predict future outcomes, and assess data quality.
These insights will drive data-driven decisions and strategic initiatives across the organization.
Using advancedstatistical analysis techniques, you will identify trends, assess data quality, and extract actionable insights across these domains, enabling the organization to make data-driven decisions that align with business objectives and KPIs.
Work closely with stakeholders to understand business objectives, translating them into data-driven solutions that align with strategic goals.
Provide contextualized insights to non-technical stakeholders, ensuring a clear connection between data findings and business impact.
Design and optimize database structures to ensure scalability, performance, and reliability within Oracle ADW and OCI environments.
This includes maintaining schema integrity, managing database objects, and implementing efficient table structures that support seamless reporting and analytical needs.
Build and manage data pipelines that automate the flow of data from diverse sources into Oracle databases, using ETL processes to transform data for analysis and reporting.
Conduct data quality assessments, identify anomalies, and validate the accuracy of data ingested into our systems.
Working alongside data governance teams, you will establish metrics to measure data quality and implement controls to uphold data integrity, ensuring reliable data for stakeholders.
Mentor junior team members and share best practices in data analysis, modeling, and domain expertise.
Job Requirements.
Solid understanding of statistical methods, hypothesis testing, data distribution, regression analysis, and probability.
Proficiency in Python for data analysis and statistical modeling.
Experience with libraries like pandas, NumPy, and SciPy.
Knowledge of methods and techniques for data quality assessment, anomaly detection, and validation processes.
Skills in defining data quality metrics, creating data validation rules, and implementing controls to monitor and uphold data integrity.
Familiarity with visualization tools (e.
., Tableau, Power BI, Oracle Analytics Cloud) and libraries (e.
., Matplotlib, Seaborn) to convey insights effectively.
Strong communication skills for collaborating with stakeholders and translating business goals into technical data requirements.
Ability to contextualize data insights in business terms and to present findings to non-technical stakeholders in a meaningful way.
Ability to cleanse, transform, and aggregate data from various sources, ensuring it’s ready for analysis.
Experience with relational database management and design, specifically in Oracle environments (e.
., Oracle Autonomous Data Warehouse, Oracle Database).
Skills in designing, maintaining, and optimizing database schemas to ensure efficiency, scalability, and reliability.
Advanced SQL skills for complex queries, indexing, stored procedures, and performance tuning.
Experience with ETL tools such as Oracle Data Integrator (ODI), or other data integration frameworks.
Expertise in Git, including branching strategies, code reviews, and collaboration tools such as GitHub or GitLab.
Qualifications.
10+ years of experience in data engineering and analytics, with a strong background in designing scalable database architectures, building and optimizing data pipelines, and applying statistical analysis to deliver strategic insights across complex, high-volume data environments.
Experience leading technical initiatives, mentoring junior engineers, and driving architectural decisions.
Strong analytical and problem-solving skills with the ability to resolve complex technical challenges.
Bachelor’s or master’s degree in computer science, Engineering, or a related field, or equivalent practical experience.
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Oracle is an Equal Employment Opportunity Employer*.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law.
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