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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data engineering, including proficiency in ETL processes, data pipeline development, and cloud services platforms such as GCP, Azure, or AWS. Strong ability to synthesize data from various sources and present analytical findings to stakeholders.
Highest-signal resume keywords
ETL ProcessesData Pipeline DevelopmentCloud Services (GCP, Azure, AWS)Python ProgrammingData Warehousing Solutions
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonJavaScalaC++SQLPySparkData Engineering DocumentationData APIsData StructuresAlgorithms
Soft Skills
Strong Communication SkillsStakeholder ManagementTeam CollaborationAnalytical ThinkingStorytelling
Tools & Technologies
DatabricksPower BIDelta LakeBusiness Intelligence PlatformsData Governance Tools
Industry Keywords
Data Life CycleData InterconnectionsData OptimizationMachine Learning AlgorithmsDistributed Systems
Tech Stack
Tools & technologiesAWSAzureCloudDistributed SystemsETLGoogle Cloud PlatformJavaPySparkPythonScalaSQLUnityC++
About the role
Key responsibilities & impact- Supervise and support data engineering projects and build solutions using software/application development knowledge
- Develop and deliver data engineering documentation
- Gather requirements, define scope, and integrate data for data engineering projects
- Recommend analytic reporting products and tools and support emerging technology adoption
- Perform data engineering maintenance and support
- Provide implementation strategies and execute backup, recovery, and technology solutions for proof-of-concept analysis
- Perform ETL using data from various sources and load transformed data into databases or business intelligence platforms
- Build data APIs for data scientists and business intelligence analysts to query data
- Code in Python, Java, Scala, C++, or other languages used for statistical analysis and modeling
- Develop batch and real-time data pipelines supporting data science and machine learning
- Integrate internal and external data sources
- Perform ETL data conversions, data cleansing, and enrichment
- Manage the full systems life cycle, including analysis, technical requirements, design, coding, testing, and implementation
- Synthesize disparate data sources into reusable and reproducible data assets
- Contribute to data science through analytical model feature tuning
- Guide team members and present data analysis and findings to stakeholders
Requirements
What you’ll need- Literate in programming languages used for statistical modeling and analysis, data warehousing, cloud solutions, and building data pipelines
- Strong understanding of database systems and data warehousing solutions
- Strong understanding of data interconnections between operational and business functions
- Strong understanding of data life cycle stages, including collection, transformation, analysis, secure storage, and accessibility
- Strong understanding of scalable data environments, including data throughput, large-scale data analysis, real-time predictions, security, regulations, and compliance
- Strong knowledge of algorithms, data structures, data filtering, and data optimization
- Strong understanding of analytic reporting technologies and environments, such as PBI
- Strong understanding of a cloud services platform such as GCP, Azure, or AWS
- Proficiency in Databricks notebooks using Python, SQL, and PySpark for data transformation, modeling, and analysis
- Strong communication and storytelling skills for presenting complex data concepts in clear, non-technical language
- Experience working with cross-functional teams across product, operations, finance, marketing, and compliance
- Understanding of business KPIs, metrics, and domain-specific data models
- Requirements gathering and stakeholder management experience
- Knowledge of Unity Catalog for governance, lineage, permissions, and secure data sharing
- Understanding of data versioning, ACID transactions, and time travel using Delta Lake
- Understanding of machine learning algorithms
- Understanding of distributed systems and the underlying business problem being addressed
- Bachelor’s degree in MIS, mathematics, statistics, or computer science, international equivalent, or equivalent job experience
- Must be currently located in the same geographic location as the job or willing to relocate yourself
- Must be a U.S. Citizen or National of the U.S., an alien lawfully admitted for permanent residence, or an alien authorized to work in the U.S. for this employer
Benefits
Comp & perks- Permanent employment
- Equal opportunity workplace free of discrimination, harassment, and retaliation