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Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformHadoopKafkaPandasScikit-LearnSparkSQL
About the role
Key responsibilities & impact- You will be part of a team responsible for supporting new and existing customers in their data engineering needs.
- You will guide customers to make the best technical decisions to achieve their goals
- You will actively work across multiple customer accounts which you would need to track and report on their progress.
- You will design, build, and operationalize complex data solutions, correct problems, apply transformations, and recommend data cleansing /quality solutions.
- You will analyze sources to determine value and recommend data to include in analytical processes.
- You will incorporate core data management competencies including data governance, data security and data quality.
- You will collaborate within and across teams to support delivery and educate end users on data products / analytic environments.
- You will perform data and system analysis, assessment and resolution for defects and incidents of moderate complexity and correct as appropriate.
- You will test data movement, transformation code, and data components.
Requirements
What you’ll need- 5+ years of related experience in data engineering and data product development.
- Experience in one or more of the following:
- - Data Engineering technologies (e.g., Spark, Hadoop, Kafka)
- - Databricks platform - data engineering and/or ML ops experience would be a huge bonus
- - Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)
- - Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)
- Solid understanding of the end to end data analytics workflow
- Proven problem solving skills including debugging skills
- Strong verbal and written communication skills
- Leadership - Intermediate leadership skills with a proven track record of self-motivation in identifying personal growth opportunities
- Excellent time management and prioritization skills. Knowledge of public cloud platforms AWS, Azure, or GCP would be a plus
- Domain Knowledge: Background working in the Financial Services industry, preferably in a banking environment.
- Regulatory Compliance: Understand industry compliance requirements and standards, specifically in banking IT landscapes
- Nice to have: Databricks Certification
Benefits
Comp & perks- Innovative Environment: Work with cutting-edge technologies and industry leaders in data engineering and AI.
- Customer Impact: Make a real difference in how businesses leverage data for strategic decision-making.
- Career Growth: Opportunities for professional development and career advancement.
- Collaborative Culture: Join a supportive team that values collaboration and knowledge sharing.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringdata product developmentSparkHadoopKafkaDatabrickspandasscikit-learnSQLdata warehousing
Soft Skills
problem solvingdebuggingverbal communicationwritten communicationleadershipself-motivationtime managementprioritization
Certifications
Databricks Certification
