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Engaged Employer

Oracle

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3.7

based on 5.2k Reviews

Video summary

2 Oracle Principal Data Engineer Jobs

Principal Data Engineer

Oracle India Pvt. Ltd.

3.7

based on 5.2k Reviews

10-15 years

Kolkata, Mumbai, New Delhi + 4 more

1 vacancy

Principal Data Engineer

Oracle

posted 29d ago

Job Role Insights

Flexible timing

Key skills for the job

Data Analysis Data Analytics Python SQL Automation Testing Machine Learning

+ 2 more

Job Description

As a member of this team, the engineer will be responsible for researching and obtaining data relevant to customer success and for analyzing, designing, implementing, and testing software that drives estimates of customer success and continued renewal. The position and the project are critical to Oracle s future success with SaaS customers, especially with respect to renewals based on that success.

We are seeking a highly experienced Principal Data Engineer with a strong background in Java, SpringBoot, Oracle Database Programming, Python, and Machine Learning. The ideal candidate will have extensive experience in data engineering, data architecture, and cloud technologies, along with the ability to drive data-driven decision-making across the business. You will work closely with cross-functional teams to develop scalable pipelines and implement advanced data models.

Career Level - IC5

The principal data engineer s responsibilities include:

Analyzing and interpreting complex datasets to generate insights that directly influence business strategy and decision-making. You will apply advanced statistical analysis and predictive modeling techniques, such as machine learning and time-series forecasting, to identify trends, predict future outcomes, and assess data quality. These insights will drive data-driven decisions and strategic initiatives across the organization.
Using advanced statistical 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.
Strong understanding of business goals and domain expertise, allowing you to collaborate effectively with stakeholders to translate these goals into actionable data requirements and analytical solutions that align with our broader organizational objectives.
Write and optimize code in Java (SpringBoot), Python, and SQL for data analysis, processing, and automation.
Develop and optimize data models for Machine Learning applications.
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.
Write and optimize code in Java (SpringBoot), Python, and SQL for data analysis, processing, and automation.
Develop and optimize data models for Machine Learning applications.
Implement Python-based solutions for data science, visualization, and advanced statistical analysis.
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.g., Tableau, Power BI, Oracle Analytics Cloud) and libraries (e.g., Matplotlib, Seaborn) to convey insights effectively.
Develop and present insightful data visualizations and reports to drive decision-making.
Translate complex data into actionable business insights using structured problem-solving frameworks.
Act as a subject matter expert to support business stakeholders in solving complex data-related problems.
Familiarity with usage, operations, and commercial data sets, with an understanding of how these areas drive business outcomes.
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.g., 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.
Proven expertise in Java, SpringBoot, Oracle Database, and SQL.
Strong proficiency in Python for data science, analysis, and machine learning.
Hands-on experience with data warehousing, ETL pipelines, and data modeling.
Strong background in machine learning (e.g., regression, decision trees, classification).
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.

Employment Type: Full Time, Permanent

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