Full Stack Engineer - Java

Senior Data Engineer

Data Scientist

Data Engineer / Senior / Supervisor

ASC - Downstream Data Scientist

Software Developer

Responsibilities: Full Stack Development:&nbsp; <ul><li>Design, develop, and maintain scalable Java-based applications using Spring Boot and other Java frameworks.</li></ul> Backend Development:&nbsp; <ul><li>Implement and optimize server-side logic, ensuring high performance and responsiveness to requests from the front-end.</li></ul> Frontend Development:&nbsp; <ul><li>Work with front-end technologies to create dynamic and responsive user interfaces.</li></ul> Database Management:&nbsp; <ul><li>Develop and manage complex queries and stored procedures using Oracle Database, ensuring data integrity and security.</li></ul> System Integration:&nbsp; <ul><li>Collaborate with cross-functional teams to integrate different modules and systems seamlessly.</li></ul> Code Review &amp; Optimization: <ul><li>Conduct regular code reviews and optimize existing code to improve application performance and maintainability.</li></ul> Troubleshooting &amp; Debugging: <ul><li>Identify, troubleshoot, and resolve complex software issues in a timely manner.</li></ul> Documentation: <ul><li>Create and maintain detailed technical documentation to support the development process.</li></ul> Requirements: <ul><li>Bachelor’s degree in computer science, Information Technology, or related field.</li><li>5-8 years of relevant experience.</li></ul> Mandatory skills <ul><li>Full Stack Development: Proficient in both front-end and back-end technologies, with a focus on Java Full Stack development and enterprise security best practices</li><li>Java/J2EE: Strong expertise in Java programming and J2EE architecture.</li><li>Spring Boot: Extensive experience in using Spring Boot for developing microservices and RESTful APIs.</li><li>Oracle Database: Solid experience with Oracle databases, including writing and optimizing SQL queries.</li><li>Front end technology skills – ReactJS or AngularJS experience&nbsp;</li><li>Desired/ Secondary skills</li><li>Experience in Unix / Linux / Mac environment</li><li>Exposure to cloud environments / AWS &amp; DevOps tools and techniques</li><li>Strong problem-solving skills and the ability to work independently and in a team environment.</li><li>Excellent communication skills and the ability to work effectively with cross-functional teams.</li></ul>

Responsibilities: <ul><li>Develop and maintain data pipelines for efficient extraction, transformation, and loading (ETL) processes.</li><li>Design and optimize data storage solutions, including Amazon Redshift data warehouses and Amazon S3 data lakes</li><li>Ensure data quality and integrity through validation, cleansing, and error handling processes.</li><li>Collaborate with data analysts, data architects, and software engineers to understand data requirements and deliver relevant data sets for business intelligence.</li><li>Implement data security measures and access controls to protect sensitive information.</li><li>Automate and improve data processes and workflows for scalability and efficiency.</li><li>Monitor data infrastructure performance and address any issues promptly.</li><li>Stay updated on industry trends and emerging technologies in data engineering.</li><li>Document data pipelines, processes, and best practices to facilitate knowledge sharing.</li><li>Continuously optimize data architecture to support the companys evolving data needs.</li><li>Work cross-functionally to drive data-driven decision-making within the organization.</li></ul> Requirements: <ul><li>Bachelors degree in Computer Science, Information Technology.</li><li>Minimum 6 years of experience in data engineering - CS</li><li>Knowledge of AWS services, particularly Glue, Redshift and S3.</li><li>Data Storage and Management - Amazon S3, Amazon RDS and DynamoDB</li><li>Data Processing and ETL - AWS Glue</li><li>Data Warehousing - Amazon Redshift</li><li>Programming and Scripting:</li><li>Proficiency in languages like Python, Java, or Scala for data manipulation and automation.</li><li>Data Modeling and Architecture&nbsp;</li><li>Monitoring and Optimization - Using AWS CloudWatch for monitoring and optimizing data workflows</li><li>Proficiency in SQL and database management.</li><li>Experience with ETL (Extract, Transform, Load) processes.</li><li>Familiarity with data warehousing and cloud platforms (AWS, Azure, or Google Cloud).</li><li>Strong data modeling skills</li></ul>

Responsibilities: <ul><li>Implement business process improvements - automating manual processes, optimizing data delivery, redesign/restructure data and process flows for more efficiency.</li><li>Develop expertise and aim to become a subject matter expert on the entire data, analytics and process automation ecosystem.</li><li>Bridge process and technology gaps with innovative solutions using a variety of tools (e.g. Power Automate, Python, PowerApps, Selenium, SQL, UI Path etc.)</li><li>Develop and maintain ETL (Extract, Transform, Load) processes for data management.</li><li>Create visually appealing, intuitive and insightful dashboards and reports using data visualization tools (e.g. Power BI, Tableau).</li><li>Utilize statistical techniques to solve business problems and provide insights.</li><li>Present findings and recommendations to stakeholders in a clear and concise manner.</li><li>Collaborate with cross-functional teams to understand their data and process needs and provide analytical and digitization support.</li><li>Collaborate with DBAs, IT and Architecture teams as required</li><li>Be heavily involved in development and testing of newly integrated data sources and/or environments</li><li>Document data processes, methodologies, and analysis techniques for future reference and training purposes.</li></ul> Requirements: <ul><li>Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Industrial Engineering or a related field.</li><li>2+ years of experience as a Data Analyst, Digital Transformation Analyst or in a similar analytical/technical role preferably in a procurement or supply chain environment.</li><li>Experience with automation tools such as Power Automate, PowerApps, UI Path, Python, Selenium etc.</li><li>Experience with creating and managing databases in AWS, SQL Server, Oracle etc. and working with APIs to integrate systems.</li><li>Possess transferrable programming skills in any language (e.g. Python, C++, JavaScript etc.)</li><li>Proficiency in SQL for database querying and manipulation.</li><li>Experience with statistical analysis software (e.g., R, Python).</li><li>Experience with data visualization tools (e.g., Tableau, Power BI).</li><li>Knowledge of Excel at an advanced level (Power query, macros).</li><li>Demonstrable willingness to learn new tools and technologies.&nbsp;</li><li>Strong analytical and critical thinking abilities.</li><li>Ability to explain technical processes to non-technical audiences.</li><li>Attention to detail and a proactive approach to problem-solving.</li><li>Ability to manage multiple projects and meet deadlines in a fast-paced environment.</li><li>Knowledge of machine learning algorithms and data modelling techniques.</li></ul>

Role Description:The Data Engineering Senior Supervisor will lead a small team of data engineering professionals to design, build and operate high performance data centric products or solutions through the use of modern engineering practices and technologies.In this role, you will provide guidance to ensure the delivered data centric products or solutions are scalable, sustainable and robust.You will also lead team development and cross team relationships and delivery to advance the company's engineering delivery.Responsibilities:Lead a local or regional team of engineering professionals that design, develop, deploy and enhance new and existing data centric products or solutions through the use of modern platforms and technologies.Provide routine inputs and guidance to the data engineering team on business requirements analysis, technical specification's preparation, product delivery, testing and operation to support businesses strategic direction.Coach engineers, share relevant technical approaches, identify new trends, modern skills and present new methodologies within the data engineering community.Lead and develop a team, coach and make decisions related to talent management, hiring, performance, and disciplinary actions.Other duties as assignedRequirements:Minimum QualificationsBachelor's degree in a related field or equivalent experience.Minimum of four years of related work experience.Minimum of two years leading a team of Data Engineers.Preferred QualificationsConfirmed data engineering experience with data storage and management of large, heterogenous datasets, including formats, structures, and cataloging with such tools as Iceberg, Parquet, Avro, ORC, S3, HFDS, HIVE, Kudu or others.Experience leading Big Data engineering teams working in environments such as Hadoop and SparkExperience leading technology strategies with cloud Platforms including AWS, GCP or AzureExperience leading engineering teams working in streaming and stream integration or middleware platforms, tools, and architectures such as Kafka, Flink, JMS, or Kinesis.Confirmed knowledge of best practice patterns and how to apply them to modern data architectures, including data warehouses, data lakes, data mesh, hubs and associated capabilities including ingestion, governance, modeling, observability and more.Experience leveraging transformation and modeling tools, including SQL based transformation frameworks, orchestration and quality frameworks including dbt, Apache Nifi, Talend, AWS Glue, Airflow, Dagster, Great Expectations, Oozie and others.Strong programming knowledge of SQL, Python, R, Java, Scala or equivalent.Proficiency in engineering tooling including docker, git, and container orchestration services.Strong experience leading devops teams with demonstratable understanding of associated best practices for code management, continuous integration, and deployment strategies.Experience and knowledge of data governance considerations including quality, privacy, security associated implications for data product development and consumption.A passion for quality and continuous improvement with an owners mindset.Ability to work effectively as part of a team, group and cultureAbility to navigate ambiguity and work in agile ways.

Responsibilities:Formulates and leads guided, multifaceted analytic studies against large volumes of data.Interprets and analyzes data using exploratory mathematic and statistical techniques based on the scientific method.Coordinates research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data.Experiments against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.Leads all data experiments tasked by the Data Science Team.Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts.Develops methodology and processes for prioritization and scheduling of projects.Analyzes problems and determines root causes.Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models.Works closely with all business units and engineering teams to develop strategy for long term data platform architecture.Requirements:Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields5-7 years of professional experienceProficient with one or more programming languages (Java, C++, Python, R, etc.)Demonstrated experience applying data science methods to real-world data problemsExperience utilizing visualization tools to take advantage of the growing volume of available informationData Scientist Qualifications / Skills:Advanced analytical knowledge of dataConducting big data analysisData conditioningProgramming advanced computingDeveloping algorithmsDeveloping software and data modelsExecuting predictive analytics

Responsibilities:We offer you a diverse range of tasksAnalysis, design and implementation of software as part of our engineering tools.Implementation of various components based on specifications.Maintenance and servicing of existing applications.Creation of development documentation.Collaboration in scrum and project teams.Close cooperation with external development teams.Requirements:Completed IT studies (university / FH) or equivalent training.Several years of professional experience as a software developer.Very good knowledge of Visual Studio .NET (C#, Visual Basic) and in handling relational databases (MS SQL Server, MS Access, SQLite, LINQ, Entity Framework).Familiar with the modeling language UML and current principles of software development, such as software development, such as "clean code" developmentKnowledge of CorelDRAW, XML and GitHub and agile software development methods an advantage.Team player.Enthusiastic about technology and willing to learn.Structured and independent way of working.Very good knowledge of German and English.We are looking for committed, innovative and solution-oriented applicants.

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Full Stack Engineer - Java

Senior Data Engineer

Data Scientist

Data Engineer / Senior / Supervisor

ASC - Downstream Data Scientist

Software Developer

WhiteCrow
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Full Stack Engineer - Java

Senior Data Engineer

Data Scientist

Data Engineer / Senior / Supervisor

ASC - Downstream Data Scientist

Software Developer

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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