Lavu Tech Solutions Hiring! Full Time Sr. Data Engineer (AI-ML) in Federal Territory - Ricebowl

Visa sponsorship available.

Responsibilities

Data Product Engineering Design and build data pipelines ETL processes from multiple sources to ensure data is easily accessible for stakeholders to support AI and Advanced Analytics requirements.

Data Quality Ensure high data quality and implement monitoring systems to detect and resolved data discrepencies

Technology Evaluation Research and evaluate new technologies and tools for data integration analytics and visualization proposing innovative solutions to improve data integration and analysis capabilities

Cloud Technologies Design build and maintain data product solutions using cloud platforms like AWS Azure or GCP ensuring efficient utilization of cloud resources and adherence to security and compliance standards

Advanced Data Visualization Advocate for the adoption of advanced data visualization tools and techniques empowering business users and data analysts to explore and communicate data insights effectively

SelfService Analytics Develop and maintain selfservice analytics capabilities enabling users across the organization to access and analyze data independently fostering datadriven decisionmaking

Knowledge Repository Establish a comprehensive knowledge repository for reusable data assets including datasets data models code libraries and best practices to promote data sharing and collaboration among teams

Collaborative Partnerships Collaborate closely with data scientists data architects data analysts software engineers and business stakeholders to understand data requirements and deliver data solutions that address their needs effectively

Performance Optimization Continuously monitor and optimize data pipelines ETL jobs and realtime data processing workflows to ensure optimal performance and minimal latency

Documentation and Training Create and maintain comprehensive technical documentation guidelines and training materials to support data engineering and data science practices

Qualifications

 Bachelors or Masters degree in Computer Science Data Science Information Systems or a related field

 5 to 10 years of experience in data engineering or data science roles preferably within the banking or financial industry

 Strong background supporting AIML model development feature engineering and model deployment with a track record of implementing machine learning solutions in realworld scenarios

 Indepth knowledge of BI tools such as Denodo OAS Power BI or similar platforms for data visualization and reporting

 Proficiency in cloud technologies such as AWS Azure or GCP with handson experience in building cloudbased data solutions and leveraging realtime analytics capabilities

 Expertise in data engineering concepts including data pipelines APIs ETL processes and data integration frameworks

 Familiarity with advanced data visualization tools like OAS Power BI or similar platforms

 Solid understanding of data governance data quality and data security principles

 Programming skills in languages like Python SQL or Java with experience in working with large datasets and distributed computing frameworks eg Spark

 Strong analytical and problemsolving skills with a detailoriented and proactive approach

 Excellent communication and interpersonal skills capable of effectively conveying technical concepts to nontechnical stakeholders

 Self motivated and capable of working both independently and as part of a team