Data Analyst

• Practice Data

• Technologies Business Intelligence Jobs and Data Recruitment

• Location Warszawa, - None Specified -

• Type Contract

Your key responsibilities

• Data Extraction and Standardization: Lead initiatives to extract and standardize financial data from various formats, including PDF, HTML, XBRL and iXBRL, ensuring data accuracy and consistency.
• Mentorship and Development: Provide guidance and support to junior analysts, fostering their growth in data analysis, programming, and statistical methodologies.
• Exploratory Data Analysis: Conduct exploratory data analysis to identify trends, raise important questions, and derive actionable insights.
• Data Model development: Design, implement and optimize conceptual, logical and physical data models for enterprise-scale data products. Develop and maintain data models using ERD diagrams and manage the data dictionaries, for transactional, star and flat schemas etc for different storage structures.
• Data Model Democratization: Partner with data engineering teams to democratize the data model for designing efficient data pipelines.
• Data Modelling Standards: Define and enforce data modelling standards and best practices. Conduct data analysis to validate modelling standard compliance, model accuracy, identify anomalies, and ensure data quality.
• Data Classification and Taxonomies: Design custom taxonomies, and reference data classification methods/structures
• Programming and Automation: Utilize programming languages such as Python, Spark, Regex, Shell Scripts and SQL for data manipulation, analysis, and automation of processes, including meta-programming and dynamic code generation.
• Database Management: Manage and optimize databases (SQL Server, Neo4j, Snowflake, Postgres), understanding join types, aggregate functions, and data storage formats (Parquet, AVRO, Delta).
• Collaboration: Collaborate with product managers, data engineers, and analysts to translate business requirements into robust data structures. Work closely with cross-functional teams to address data quality issues and implement effective solutions, promoting a culture of continuous improvement.

Skills and attributes for success

• Highly skilled in data modelling: Experience developing data models from scratch for green field projects in multiple domains. Should have Deep understanding of data warehousing concepts, dimensional modelling, and normalization/denormalization techniques. Expertise in tools such as Erwin Data Modeler, PowerDesigner, or similar.
• Knowledge of data products: Strong understanding of data product design principles and lifecycle.
• Strong SQL skills and experience with relational (e.g., Oracle, SQL Server, PostgreSQL) and cloud databases (e.g., Snowflake, BigQuery, Redshift).

• Good understanding of Azure cloud data services (Data Lake, Data Factory, Azure SQL).

• Problem-Solving: Adept at tackling complex issues and finding effective solutions.
• Curiosity and Self-Starter: Always eager to learn and take initiative without needing constant guidance.
• Comfortable with Ambiguity: Capable of working efficiently even when the answers are not immediately clear.
• Effective Communication: Excellent at conveying complex ideas and collaborating with stakeholders.
• Experience with Databases and Data Formats: Familiar with various databases, operating systems, file types, and data formats.
• Experience with different data roles (analysis, modelling, science, etc).

Preferred Skills: 

• Advanced Data Modelling Techniques: Experience with advanced modelling.
• Business Analysis Expertise: Ability to bridge the gap between technical and business requirements.
• Exposure to Programming: Skilled in Python, Spark and SQL.
• Project Management: Skills in managing projects, timelines, and deliverables.
• Data Visualization Tools: Proficiency with tools such as Tableau, Power BI, or similar.

Qualifications: 
 

• Bachelor’s degree in computer science, Information Technology, or equivalent 

• 5+ years of experience in data management 

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