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Regular Data Engineer

Remote United States, United States Of America (Remote)

Regular Data Engineer

1 Hour ago • All levels • Data Analyst • Artificial Intelligence

About the job

Summary

As a Data Engineer, you'll develop data & analytics solutions using vast datasets from various consumer-focused companies. You'll design high-performance algorithms, cutting-edge analytical techniques (machine learning, AI), and intuitive workflows for data insights. Responsibilities include collaborating with cross-functional teams, designing and developing robust machine learning models, cleaning/pre-processing data, implementing end-to-end ML pipelines, selecting appropriate ML techniques, performing exploratory data analysis, evaluating/fine-tuning models, deploying models into production, integrating solutions into applications, staying updated on ML advancements, and documenting solutions. You will work with big data technologies like Hive/Impala, Python, Java, Kafka, Spark, and R.

15 skills required for this role

Test your skills to join the top 1% applicants for this job

algorithms

spark

python

sql

java

azure

aws

hadoop

communication

shell

tensorflow

scala

ci-cd

github

deep-learning

Must have:

Bachelor's degree in relevant field
Proven ML engineering experience
Strong programming (Python, R)
Understanding of ML algorithms
Experience with ML libraries
Data preprocessing & visualization
Cloud platform experience (AWS, Azure, GCP)
Version control (Git)
Problem-solving & communication skills
Teamwork & project completion

Good to have:

Python/Scala, Spark, SQL, Hadoop
Java, Spring Boot, JUnit
Software testing approaches
RESTful APIs & microservices
CI/CD experience
SQL databases (Postgres, Oracle)
Hadoop tools (Hive, Impala, Spark)
Data pipeline tools (NIFI, Airflow)
Shell scripting
Database/ETL performance tuning
Cloud APIs (Azure, AWS)
Agile experience

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Project description

As a DataEngineer 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 required

Skills

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

Ability 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

Other

Languages

English: C1 Advanced

Seniority

Regular

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About The Company

Luxoft

1227 Active Jobs

Luxoft, a DXC Technology Company (NYSE: DXC), is a digital strategy and software engineering firm providing bespoke technology solutions that drive business change for customers the world over. Acquired by U.S. company DXC Technology in 2019, Luxoft is a global operation in 44 cities and 21 countries with an international, agile workforce of nearly 18,000 people. It combines a unique blend of engineering excellence and deep industry expertise, helping over 425 global clients innovate in the areas of automotive, financial services, travel and hospitality, healthcare, life sciences, media and telecommunications.

DXC Technology is a leading Fortune 500 IT services company which helps global companies run their mission critical systems. Together, DXC and Luxoft offer a differentiated customer-value proposition for digital transformation by combining Luxoft’s front-end digital capabilities with DXC’s expertise in IT modernization and integration. Follow our profile for regular updates and insights into technology and business needs.