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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing cloud-based data solutions, particularly within AWS environments, while providing technical leadership and mentorship to data engineering teams. Proficient in developing complex data pipelines and integrating data solutions to support business intelligence and AI initiatives.
Highest-signal resume keywords
Data ArchitectureAWS Cloud ServicesPython ProgrammingData Pipeline DesignLeadership
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringCloud-Based Data SolutionsAWS RedshiftAWS GlueAWS AthenaAWS EMRData LakesData WarehousingAirflowSpark
Soft Skills
LeadershipTeamworkAnalytical SkillsSelf-LearningInitiative
Tools & Technologies
DockerECSKubernetesQuickSightTableauPowerBI
Industry Keywords
Enterprise DWHData SolutionsMachine LearningGenAIPrompt Engineering
Tech Stack
Tools & technologiesAirflowAmazon RedshiftAWSCloudDockerKubernetesMicroservicesPythonSparkTableau
About the role
Key responsibilities & impact- Lead the architectural design and implementation of the new enterprise DWH project
- Design, develop, and optimize complex cloud-based data solutions for processing massive datasets
- Select and implement optimal AWS services and data formats for the core data stack
- Establish the technological roadmap for the enterprise DWH project
- Provide technical leadership, mentorship, and professional guidance to the Data Engineering team
- Collaborate with development teams, Data Scientists, and end-users to define requirements and deliver innovative Data and AI solutions
- Enable large-scale data processing to support BI and AI initiatives
Requirements
What you’ll need- B.Sc. in Computer Science, Engineering, Mathematics, or Statistics
- Proven experience of several years as a Data Architect, with a strong background as a Data Engineer focusing on Python and Spark
- Deep expertise in planning and designing AWS cloud environments
- Experience with AWS Redshift, Glue, Athena, EMR / EMR Serverless, and RDS
- Proven experience designing complex data pipelines using Airflow / Step Functions
- Experience with microservices architecture based on Docker, ECS, and Kubernetes
- Expertise in large-scale analytical data structures, optimizing partitions, and building Data Lakes / DWH using Parquet and Iceberg
- Experience integrating data solutions with QuickSight, Tableau, and PowerBI
- Familiarity with Machine Learning platforms
- Experience designing architectures supporting GenAI / Prompt Engineering solutions
- Initiative and independence
- Strong leadership and teamwork capabilities
- Self-learning ability
- High analytical skills
- Must pass a computerized reliability test, security interview, and polygraph test
Benefits
Comp & perks- Competitive salaries
- Bonus incentives
- Benefits
- Flexible hours
- Mentoring
- Learning and personal development opportunities