Lorven Technologies
Regular Data Engineer
Lorven Technologies, Chicago, Illinois, United States, 60290
Role: Regular Data Engineer
Location: Remote
Project description
As a Data Engineer in the Data Engineering & Analytics team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data. You will have the opportunity to develop data-driven innovative analytical solutions and identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations/decisions through activities like building ML models, automated data pipelines, designing data architecture/schema, performing jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Java, Kafka, Spark, R, etc.Responsibilities
Collaborate with cross-functional teams to understand business requirements and translate them into machine learning solutions
Design and develop robust machine learning models and algorithms that solve complex business problems
Design and develop data and analytics solutions that sit atop vast datasets
Clean, preprocess, and analyze data to ensure its suitability for machine learning applications
Implement end-to-end machine learning pipelines, from data collection and feature engineering to model training and deployment
Select appropriate machine learning techniques and algorithms based on the problem's requirements and constraints
Perform exploratory data analysis and generate insights to guide model development
Evaluate and fine-tune machine learning models for performance, accuracy, and reliability
Deploy machine learning models into production environments, ensuring scalability and maintainability
Collaborate with technical team to integrate machine learning solutions into applications
Stay up-to-date with the latest advancements in machine learning and recommend innovative approaches to enhance our capabilities
Document and communicate machine learning solutions, findings, and insights to technical and non-technical stakeholders
Additional tasks as requiredSkills
Must have
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
Proven experience as a machine learning engineer, working on complex machine learning projects
Strong programming skills in languages like Python, R, or similar
Solid understanding of machine learning algorithms, deep learning frameworks, and statistical modeling techniques
Hands-on experience with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn
Proficiency in data preprocessing, feature engineering, and data visualization
Experience with cloud platforms such as AWS, Azure, or GCP for deploying machine learning models
Familiarity with version control systems (e.g., Git) and collaborative development practices
Strong problem-solving skills and ability to troubleshoot and optimize machine learning models
Excellent communication skills to convey technical concepts to both technical and non-technical stakeholders
Proven ability to work in a collaborative team environment and drive projects to completion Ideal Candidate Qualifications:
Working proficiency in using Python/Scala, Spark (tuning jobs), SQL, Hadoop platforms to build Big Data products & platforms.
Good programming skills in Java and spring boot and Junit.
Knowledge in software development test approaches & frameworks
Familiarity with RESTful APIs and micro-services architectures
Experience in working with CI/CD
Experience in working with SQL database like Postgres, Oracle
Preferably with hands-on experience with Hadoop big data tools (Hive, Impala, Spark)
Experience with data pipeline and workflow management tools: NIFI, Airflow.
Comfortable in developing shell scripts for automation.
Good troubleshooting and debugging skills.
Proficient in standard software development, such as version control, testing, and deployment
Demonstrated basic knowledge of statistical analytical techniques, coding, and data engineering
Ability to quickly learn and implement new technologies
bility to Solve complex problems with multi-layered data sets
Ability to innovate and determine new approaches & technologies to solve business problems and generate business insights & recommendations.
Ability to multi-task and strong attention to detail
Flexibility to work as a member of a matrix based diverse and geographically distributed project teams
Good communication skills
both verbal and written and strong relationship, collaboration skills, and organizational skills
Nice to have
Experience with performance Tuning of Database Schemas, Databases, SQL, ETL Jobs, and related scripts
Experience in working with Cloud APIs (e.g., Azure, AWS)
Experience participating in complex engineering projects in an Agile setting e.g. Scrum
Location: Remote
Project description
As a Data Engineer in the Data Engineering & Analytics team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data. You will have the opportunity to develop data-driven innovative analytical solutions and identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations/decisions through activities like building ML models, automated data pipelines, designing data architecture/schema, performing jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Java, Kafka, Spark, R, etc.Responsibilities
Collaborate with cross-functional teams to understand business requirements and translate them into machine learning solutions
Design and develop robust machine learning models and algorithms that solve complex business problems
Design and develop data and analytics solutions that sit atop vast datasets
Clean, preprocess, and analyze data to ensure its suitability for machine learning applications
Implement end-to-end machine learning pipelines, from data collection and feature engineering to model training and deployment
Select appropriate machine learning techniques and algorithms based on the problem's requirements and constraints
Perform exploratory data analysis and generate insights to guide model development
Evaluate and fine-tune machine learning models for performance, accuracy, and reliability
Deploy machine learning models into production environments, ensuring scalability and maintainability
Collaborate with technical team to integrate machine learning solutions into applications
Stay up-to-date with the latest advancements in machine learning and recommend innovative approaches to enhance our capabilities
Document and communicate machine learning solutions, findings, and insights to technical and non-technical stakeholders
Additional tasks as requiredSkills
Must have
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
Proven experience as a machine learning engineer, working on complex machine learning projects
Strong programming skills in languages like Python, R, or similar
Solid understanding of machine learning algorithms, deep learning frameworks, and statistical modeling techniques
Hands-on experience with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn
Proficiency in data preprocessing, feature engineering, and data visualization
Experience with cloud platforms such as AWS, Azure, or GCP for deploying machine learning models
Familiarity with version control systems (e.g., Git) and collaborative development practices
Strong problem-solving skills and ability to troubleshoot and optimize machine learning models
Excellent communication skills to convey technical concepts to both technical and non-technical stakeholders
Proven ability to work in a collaborative team environment and drive projects to completion Ideal Candidate Qualifications:
Working proficiency in using Python/Scala, Spark (tuning jobs), SQL, Hadoop platforms to build Big Data products & platforms.
Good programming skills in Java and spring boot and Junit.
Knowledge in software development test approaches & frameworks
Familiarity with RESTful APIs and micro-services architectures
Experience in working with CI/CD
Experience in working with SQL database like Postgres, Oracle
Preferably with hands-on experience with Hadoop big data tools (Hive, Impala, Spark)
Experience with data pipeline and workflow management tools: NIFI, Airflow.
Comfortable in developing shell scripts for automation.
Good troubleshooting and debugging skills.
Proficient in standard software development, such as version control, testing, and deployment
Demonstrated basic knowledge of statistical analytical techniques, coding, and data engineering
Ability to quickly learn and implement new technologies
bility to Solve complex problems with multi-layered data sets
Ability to innovate and determine new approaches & technologies to solve business problems and generate business insights & recommendations.
Ability to multi-task and strong attention to detail
Flexibility to work as a member of a matrix based diverse and geographically distributed project teams
Good communication skills
both verbal and written and strong relationship, collaboration skills, and organizational skills
Nice to have
Experience with performance Tuning of Database Schemas, Databases, SQL, ETL Jobs, and related scripts
Experience in working with Cloud APIs (e.g., Azure, AWS)
Experience participating in complex engineering projects in an Agile setting e.g. Scrum