Role Summary
As a Senior Analytical Engineer you will be a core member of the data architect team responsible for transforming raw data into high-quality actionable insights. Your mission is to build own and maintain the data products that power our analytics reporting and business decisions. You will work across the entire data lifecycle from data ingestion to delivering final insights ensuring data quality and governance are central to everything you build.
This role requires a unique blend of technical expertise in data modeling data pipelines data quality a strong business acumen to understand complex problems and exceptional communication skills to collaborate with diverse teams. You will act as the key link between our data science engineering product and the business driving value by making data trustworthy and accessible.
Whats On Your Plate
As an Analytical Engineer and Data Architect you will be responsible for:
1. Data Product Development & Ownership
Build and Maintain: Design build and maintain enterprise data warehouses and analytical data marts.
Translate Needs: Work closely with data scientists product managers and business teams to understand their problems and translate complex business requirements into robust data models and data products.
End-to-End Responsibility: Take full ownership of data products from concept to production ensuring they are scalable reliable and well-documented.
2. Data Quality & Governance
Enhance Data Quality: Implement and enforce data quality and governance standards throughout the data pipeline moving checks and enrichment upstream.
Root Cause Analysis: Proactively identify data quality and governance shortfalls perform root cause analysis and implement solutions with monitoring mechanisms.
3. Cross-Functional Collaboration
Collaborate: Partner with data engineers to ensure smooth data ingestion from source systems and with backend engineers to define and implement data contracts.
Consult: Serve as a subject matter expert for analytical and business teams guiding them on best practices for data consumption and model design.
4. Data Pipeline & Modeling Expertise
Pipeline Management: Design and optimize data pipelines to support data transformation data structures metadata and dependency management.
Modern Modeling: Apply a variety of data modeling techniques including modern methods to build efficient and flexible data solutions.
Qualifications :
What Did We Order
Experience: 5 years of experience in data management with a strong focus on analytical engineering.
Technical Skills: Advanced SQL knowledge and experience with relational and non-relational databases. Proficient in building and optimizing data pipelines and analytical data models.
Data Modeling: Solid experience with various data modeling techniques including modern methodologies.
Center of Excellence: Build best practices and processes supporting data transformation data structures metadata dependency and workload management.
Problem-Solving: A strong problem-solver with a figure it out growth mindset and a keep it simple approach.
Collaboration: Proven ability to work effectively with cross-functional teams in a dynamic environment. Excellent collaborator and communicator who can translate business needs into technical solutions.
Ownership: A strong sense of ownership and accountability for data products and their impact.
Education: Bachelors degree in engineering computer science technology or a similar field.
Remote Work :
No
Employment Type :
Full-time
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Yokogawa
Hilton