with deep expertise in Oracle technologies to join our team. In this role, you will design and implement scalable data pipelines, operationalize machine learning models, and support advanced analytics solutions using Oracle databases and cloud platforms.
You will collaborate closely with data scientists, analysts, and IT teams to deliver high-performance, AI-driven systems that are deeply integrated into our Oracle-based infrastructure.
About Enigen
Enigen is a multi-award-winning Oracle Partner, deliver digital transformation projects based on Oracle applications and technology in the Oracle Cloud.
With over 15 years' experience, Enigen has one of the largest portfolios of customers implementing Oracle.
Key responsibilities include:
Oracle- Based Data Engineering
Design and implement secure data pipelines to ingest and process unstructured (RFQs, specifications, datasheets) and structured (pricing, product master, past quotes) data into respective OCI Data Storages.
Use OCI Data Integration (such as GoldenGate) for data movement and synchronization between CPQ, ERP, and RFQ repositories.
Implement data partitioning and indexing strategies in OLTP/OLAP real-time analytical Lakehouse's, for high-performance querying across RFQ and quote datasets.
Establish metadata, lineage, and governance for all AI/ML training data.
AI/ML Engineering
Apply OCI Document Understanding and OCI Generative AI for various sales process parsing, specification extraction, and draft proposal generation.
Use DB with inbuilt AutoML to train, evaluate, and deploy ML models (e.g., classification, anomaly detection, regression for cost estimation) directly inside the Database.
Integrate ML results from Lakehouse's with OCI Data Science pipelines when advanced NLP or LLM fine-tuning is required.
Build Intelligent Search solutions using OCI Vector Search and align with DB datasets for federated querying.
Integrate AI/ML deliverables (extracted specs, datasheets, quote drafts) into Oracle SaaS workflows via REST APIs, Oracle Integration Cloud (OIC), and event-driven services.
Solution Architecture & Operations
Work with Solution Architects to define both the logical and physical data components, applications and technical systems (i.e., HeatWave for scalable ML & analytics on operational data, ADB for complex reporting, data warehousing, and compliance workloads).
Implement MLOps pipelines in OCI Data Science and HeatWave AutoML for continuous model improvement.
Define monitoring, logging, and accuracy thresholds for both HeatWave and OCI AI services.
Ensure compliance across sector regulations.
The list of key responsibilities is not exhaustive, and the post holder may be required to undertake other relevant and appropriate duties as reasonably required. Travel should be expected as part of this role.
Required Experience:
Strong hands-on experience with Oracle Cloud Infrastructure (OCI), including Data Lakehouses with built in OLTP, OLAP and GenAI real-time analytics such as MySQL HeatWave and Autonomous Database
.
Must also have knowledge ofOCI Data Integration, OCI Data Science, and Generative AI services.
Expertise in MLOps pipelines, training, testing, deploying models.
Proficiency in Python, SQL, and ML frameworks.
Knowledge of natural language processing (NLP) and intelligent document processing (IDP).
Experience with SaaS API integration and Oracle Integration Cloud (OIC).
Background in ETL/ELT, high-performance SQL, and unstructured data management.
Preferred experience
:
Experience with EPC, manufacturing, or industrial sales domains.
Hands-on work with event-driven architectures on OCI (Streaming, Functions).
Familiarity with TOGAF/OAA architecture practices.
OCI and/or MySQL HeatWave certifications.
Required Qualifications:
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
3+ years of experience in data engineering and/or machine learning, with a strong focus on Oracle technologies.
Proficiency in Oracle SQL, PL/SQL, and experience with Oracle Database architecture.
Experience with Oracle Machine Learning tools or integrating external ML models into Oracle systems.
Solid understanding of data pipeline development, performance tuning, and best practices in Oracle environments.
Preferred qualifications:
Hands-on experience with
Oracle Cloud Infrastructure (OCI)
, especially services like OCI Data Science, Data Integration, and AI Services.
Familiarity with scripting languages such as
Python
or
Shell
for automation and ML integration.
Knowledge of Oracle's MLOps capabilities and DevOps practices using OCI.
Exposure to Oracle Data Lakehouse or hybrid cloud data architectures.
What we offer
A collaborative environment with opportunities for growth and mentorship.
Involvement in innovative cloud and SaaS transformation projects.
Flexible working options and supportive team culture.
Competitive compensation and professional development support
Benefits:
Private Health, Group Pension Plan, Life Assurance, Employee Assistance