Data Engineer

September 19

Apply Now

Receive Emails with Similar Jobs

Pearl Technologies Ltd

WebsiteLinkedInAll Job Openings

51 - 200

Description

• Understand the business requirements and processes around advanced analytics model execution. • Develop end-to-end data pipelines from ingestion to visual analytics with Python, SQL and Snowflake. • Good to have experience in Airflow. • Manage, enhance, maintain and support our Snowflake-based data lake. • Support our business intelligence developers to provide stunning visual analytics. • Develop, maintain and support our library of analytical functions written in Python, SQL and Snowflake. • Participate in our fast-paced, agile data iteration to deliver new capabilities in a timely manner. • Leverage key features of Snowflake for processing, entitlements, ingestion, transformation and data sharing. • Collaborate with data scientists, financial data analysts, software engineers and other data engineers to implement powerful solutions that leverage cloud, big data, NLP and ML. • Build machine learning models with advanced analytics techniques to extend our capabilities and deliver new business value. • Capture and present data-driven business insights. • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. • Work closely with software engineering teams to drive real-time model implementations and new feature creations. • Leverage existing data sources, identify and mine data from new sources, identify opportunities for and execute primary data gathering efforts, and provide recommendations on scaling new methods more broadly.

Requirements

• University degree or equivalent in data analytics, statistics, math, or computer science, with a minimum of 3 years relevant experience. • Excellent knowledge of Python and SQL. • Experience in big data processing and the development of Python and SQL for large amounts of data. • Considerable experience with unit and integration testing. • Excellent analytical, storytelling, and problem-solving skills. • Ability to translate/communicate analytics recommendations to both technical and nontechnical team members. • Strong understanding of quantitative (univariate and multivariate) analysis techniques. • Experience with predictive modelling and machine learning. • Strong experience with statistical analytical techniques, data mining, machine learning, and predictive models using Python, R or similar tools. • Experience using scripting language for collecting, organizing and manipulating data. • Ability to work with data with significant ambiguity, develop creative approaches to analytical problems, and interpret data and results from a business/industry perspective.

Benefits

• Competitive Salary • Career Growth