Azure Data Architect

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SeniorZdalnieFull-time

#472357·Dodano 2 dni temu·1

Źródło: nofluffjobs.com

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Tech Stack / Keywords

AzureData modellingData baseData warehousePython ETL PySpark R Scala

Podsumowanie oferty

As an Azure Data Architect, you will define and implement data architecture, governance, and integration solutions for the Data & Analytics domain. You will design data models and platforms, including Azure Synapse, ADF, and ADL, and develop ETL processes and data pipelines with the IT team and data experts.

Wymagania

At least 6 years of professional experience in the Data & Analytics area.
Proven experience as a Data Architect or in a similar role, ideally in a complex organizational setting.
Strong understanding of data management principles, data modeling techniques, database design, and data integration flows.
Experience developing and implementing data governance policies, procedures, and frameworks.
Familiarity with data management and governance best practices and emerging trends.
Ability to design conceptual, logical, and physical data models that meet business requirements and align with data strategy.
Strong understanding of data modeling practices, including normalization, denormalization, generalization, and performance optimization.
Expertise with relational databases such as Oracle, SQL Server, and MySQL, and NoSQL databases such as MongoDB, Cassandra, and DynamoDB.
Knowledge of database management systems, data warehousing, data integration technologies, and Big Data solutions.
Familiarity with cloud-based database, warehouse, and lakehouse platforms.
Experience designing data integration solutions, including ETL processes and data pipelines, and understanding of data integration patterns and best practices.
Understanding of Business Intelligence and data analytics requirements, and optimization of data storage and processing for reporting.
Ability to communicate technical concepts to technical and non-technical stakeholders and collaborate with cross-functional teams.
Strong analytical and problem-solving abilities to identify data-related issues and propose solutions.
Familiarity with data profiling, cleansing, harmonization, and quality assessment techniques.
Knowledge of data security and privacy regulations, such as GDPR or CCPA, and of encryption, access controls, and data masking techniques.
Must-have skills include data modelling and design, data management, requirement gathering and analysis, data processing, technical leadership, data quality, Azure Synapse, ADF, ADL, technical implementation and monitoring, and one of Python, PySpark, R, or Scala.

Nice to have:

Professional certification in data management or a related field.

Obowiązki

Provide a common business vocabulary, express strategic data requirements, and outline high-level integrated designs.
Define and implement data governance policies, procedures, and frameworks to ensure data integrity and compliance.
Collaborate with stakeholders to align data strategy with business goals and document current and target states using business-process and data-journey diagrams.
Design conceptual, logical, and physical data models that meet business requirements and align with the overall data strategy.
Define data standards, naming conventions, and classification guidelines; ensure data models are scalable, efficient, and optimized for performance.
Evaluate and select database technologies and solutions based on organizational needs.
Design and oversee data platforms, including relational and NoSQL databases, data warehouses, and Big Data solutions.
Optimize database performance, ensure data security, and implement backup and recovery strategies.
Design data integration solutions, including ETL processes and data pipelines, and document source-to-target mappings.
Collaborate with the IT team and data experts to identify data acquisition opportunities.
Follow data architecture patterns for data systems, including data lake platforms, master data management systems, and ML-enriched data flows.
Implement data profiling and cleansing processes to identify and resolve data quality issues.
Establish data quality standards and processes to measure, monitor, and improve data quality.
Facilitate discussions and workshops to gather requirements and align data initiatives with business goals; prepare data inventory documentation.
Communicate complex technical concepts to technical and non-technical stakeholders.
Stay abreast of industry trends.

Benefity

Flexible working hours.
Workation in accordance with the company’s workation policy.
Online onboarding program with a buddy from day one.
Unlimited access to the Udemy learning platform.
Certificate training programs and upskilling support, including capability development programs, knowledge-sharing sessions, webinars, and training opportunities.
Referral bonuses.
Activities to support well-being and health.
Modern office equipment, purchased for the employee or available to borrow depending on location.
Private healthcare.
Free coffee.

Elastyczne godziny

Szkolenia wewnętrzne

Opieka zdrowotna

Napoje w biurze

Premie

Lingaro

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