Company
DataEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer. Skills: Databricks, PySpark, SQL, Data Pipelines. Design, build, maintain data solutions. Develop data pipelines”
What You'll Achieve.
provide actionable insights; drive business decisions; ensure data is accessible; ensure data is reliable; ensure data is efficiently managed; meet business needs; ensure data accuracy; ensure data consistency; protect sensitive data; build scalable and efficient data solutions; meet fast-paced business needs; enable advanced analytics; enable insights; improve ETL platform performance; improve scalability; improve efficiency; ensure seamless connectivity; ensure reliability; maintain alignment; resolve issues; deliver on shared objectives
Industry & Context.
Excellent problem-solving skills; Identify and resolve complex data-related challenges; critical-thinking
work across geographic regions, global teams across time zones
What They're Looking For.
Must Have
Bachelor’s / Master’s degree, 4 to 8 years of Computer Science, IT or related field experience, Hands-on experience with big data technologies and platforms, Databricks, Apache Spark, PySpark, SparkSQL, workflow orchestration, performance tuning on big data processing, Proficiency in data analysis tools, SQL, experience with data visualization tools, Excellent problem-solving skills, ability to work with large, complex datasets, understanding of data governance frameworks, tools, and best practices
Nice to Have
Knowledge of data protection regulations and compliance requirements, GDPR, CCPA, Experience with ETL tools, Apache Spark, Python packages related to data processing, machine learning model development, understanding of data modeling, data warehousing, data integration concepts, Python, R, Databricks, SageMaker, cloud data platforms, Experience implementing automated orchestration and monitoring of data pipelines, Databricks Jobs, Apache Airflow, Familiarity with performance optimization techniques for big data processing, Spark job tuning, caching, partitioning, indexing, Exposure to multi-source integration, APIs, SQL databases, cloud storage platforms, Demonstrated ability to collaborate across global teams and time zones
What You'll Do.
maintain data solutions
Develop data pipelines
Implement ETL/ELT processes
Migrate and deploy data
Own data pipeline projects
Develop data dictionaries
Implement data security measures
Leverage cloud platforms
Build scalable data solutions
Design end-to-end data pipelines
Resolve data-related challenges
Adhere to best practices
Improve ETL platform performance
Participate in sprint planning
Design data pipelines
Engineer solutions for structured data
Engineer solutions for unstructured data
Implement automated workflows
Monitor data pipelines
Schedule data pipelines
Apply performance optimization techniques
Build integrations with data sources
Ensure connectivity and reliability
How You'll Work.
Team & Collaboration
Collaborate with cross-functional teams; Collaborate with product teams; Collaborate with Data Architects; Collaborate with Business SMEs; Collaborate with Data Scientists; Collaborate effectively with global teams; Maintain alignment; Resolve issues; Deliver on shared objectives
Communication Scope
communication; collaboration; presentation skills
Process & Methodology
manage scope, manage timelines, manage risks
Full Job Description
## **Career Category** Engineering ## ## **Job Description** _Role Description:_ The role is responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and executing data governance initiatives and visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes _Roles & Responsibilities:_ * Design, develop, and maintain data solutions for data generation, collection, and processing * Be a key team member that assists in design and development of the data pipeline * Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems * Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions * Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks * Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs * Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency * Implement data security and privacy measures to protect sensitive data * Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions * Collaborate and communicate effectively with product teams * Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast-paced business needs across geographic regions * Identify and resolve complex data-related challenges * Adhere to best practices for coding, testing, and designing reusable code/component * Explore new tools and technologies that will help to im
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