<p>Skill: Data Engineer</p> <ul> <li>Expertise implementing batch and real time data process solutions using Azure Data Lake storage, Azure Data Factor and Databricks. </li><li>Experience in built ETL pipelines for ingesting, transforming and loading data from multiple sources into Cloud data ware houses. </li><li>Proficient in Docker for containerization, utilizing REST API in Python for seamless system integration, and applying containerization concepts to improve deployment efficiency and scalability. </li><li>Experience in data extraction, data acquisition, transformation, data manipulation, performance tuning and data analysis. </li><li>Experience in Python libraries to build efficient data processing workflows and streamline ETL operations across large data sets and similar distributed systems. </li><li>Expertise in automating data quality checks, reducing data errors and ensuring more reliable reporting and analytics with data marts. </li><li>Experience in deployment activities. </li></ul> <p>Must have skills:</p> <ul> <li>Pyspark. </li><li>Python. </li><li>Data warehousing experience. </li><li>ETL Process. </li><li>Deployment experience. </li></ul> <p>Generic Managerial skills:</p> <ul> <li>Machine Learning: Experience with integrating machine learning models into data pipelines. </li><li>DevOps Practices: Familiarity with CI/CD pipelines and infrastructure as code (IaC). </li><li>Data Visualization: Knowledge of data visualization tools like Power BI, Tableau, or similar. </li><li>Soft Skills: Strong interpersonal and communication skills, with the ability to work effectively in a team environment. </li></ul> <p>Salary Range - $90,000-$120,000 a year</p> <p>#LI-NS2</p>