Senior Data Engineer
- Remote.Argentina
- Remote.Brazil
- Remote.Bulgaria
- Remote.Colombia
- Remote.Georgia
- Remote.Poland
- Rosario
- Белград
- Варна
- Варшава
- Вроцлав
- Днепър
- Ереван
- Киев
- Клуж-Напока
- Краков
- Ларнака
- Лвов
- Лодз
- Люблин
- Монтевидео
- Монтерей
- Одеса
- Рига
- София
- Тбилиси
- Харков
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Client
Project overview
Position overview
This position requires availability aligned with the EST time zone, or at least a 4-hour overlap with EST working hours (until 1 pm EST in the EU and APAC regions).
Responsibilities
- Build and maintain scalable data pipelines for ingestion into Snowflake.
- Develop and manage transformations using dbt, including modeling, testing, and comprehensive documentation.
- Design and orchestrate complex data workflows using Prefect.
- Utilize Workato to integrate and normalize data from critical SaaS platforms, including Addepar, NetSuite, Salesforce, Morningstar, and UKG.
- Design specialized data models tailored for portfolio, client, and financial reporting.
- Ensure data quality, lineage, and governance best practices while optimizing performance and costs within Snowflake.
- Partner with Tableau developers and business stakeholders to align technical delivery with reporting needs.
Requirements
- 5+ years of experience in data engineering with a focus on building modern data platforms.
- Hands-on experience with Snowflake and dbt, supported by strong SQL skills and advanced data modeling expertise.
- DBT certification.
- Proven familiarity with ETL/ELT patterns and API-based ingestion.
- Practical experience with orchestration tools such as Prefect or Airflow.
- A solid understanding of financial or wealth management data structures.
Nice to have
- Experience supporting reporting requirements for Tableau-based visualization layers.
- Experience within the Wealth Management or Investment Management sector, with specific familiarity handling investment and portfolio-related data.
- Understanding of regulatory requirements regarding financial data handling and privacy.
- Background in integrating market data providers such as Bloomberg or Morningstar.
- Advanced SQL skills and experience with Python for data engineering tasks.
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