компания "wrike" n.b. please respond in english only. as a data engineer, you will be a key member of the business technology organization with the focus on data architecture and business intelligence developing our enterprise data machine. you will be responsible for conceptualizing, designing, and building data pipelines and services, while contributing towards the evolution of our data platform as a strategic asset for driving business decisions across wrike. depending on your experience and scope you will be working on data warehousing organization, saas integrations, tooling, or practical ai implementations. we like to see people interested in more than one scope, and will gladly help to acquire extra ones. this is a highly impactful role and you will work extensively with gtm teams to translate data requirements into reliable services and data products. you must have a deep background in data engineering and a proven track record of solving complex data problems and designing long-term solutions. you will also be responsible for: own data assets and data pipelines that provide actionable insights into customer, product, gtm, and other key business functions design, develop and maintain scalable data pipelines and transformations using data from a variety of engineering and business systems (e.g., salesforce/cpq, netsuite, marketo) collaborate with analysts to improve data models that feed business intelligence tools, increasing data accessibility and drive adoption of data deploy ml models together with data science teams according to best practices of ml life cycle, and improve our ai infrastructure implement processes and systems to manage data quality, ensuring production data is always accurate and maintains slas basic qualifications: work experience building & maintaining data pipelines on data-heavy environments (data engineering, backend with emphasis on data processing, data science with emphasis on infrastructure) strong knowledge of at least one general-purpose programming language (wechr(39)re using python) advanced working sql knowledge and experience working with relational databases good communication, collaborative demeanor and ability to work in distributed, multi-functional, multinational teams with the ability to articulate a point of view. advanced english level preferred qualifications: experience with data warehousing solutions (bigquery, redshift, snowflake, vertica, or similar) experience with data pipeline orchestration (airflow, dagster, prefect, or similar) experience with major b2b vendor integrations (salesforce/cpq, netsuite, marketo, etc.) good understanding of data modelling (kimball, inmon, scds, data vault, anchor) confidence in using git, ci\cd, and containerization knowledge of python data libraries (pandas/scipy/numpy/sci-kit learn/tf/pytorch) experience with mlops and ai platforms (vertex ai, databricks, mlflow, or similar) experience with data streaming and cdc (google pub/sub, google dataflow, apache kafka, kafka streams, apache flink, spark streaming, or similar) experience with data quality tools, monitoring and alerting experience with enterprise data governance, master data management, data privacy and security (gdpr, ccpa) experience with building analytic solutions in a b2b saas environment experience partnering with go-to-market, sales, customer success, and marketing teams
Адрес
Санкт-Петербург