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Snowflake Data Engineer

unlimited holidays - extra holidays - extra parental leave - long remote period allowed
Remote: 
Full Remote
Experience: 
Senior (5-10 years)
Work from: 

Offer summary

Qualifications:

At least 8 years of IT experience and 4 years in data management, Certification in Snowflake HDInsights, Cosmos is a plus.

Key responsabilities:

  • Build Data Pipelines
  • Drive Automation through metadata management
  • Track data consumption patterns
  • Collaborate across departments
  • Ensure compliance and governance during data use
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Keylent Inc Information Technology & Services SME https://www.keylent.com/
201 - 500 Employees
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Job description

Visa status: U.S. Citizens and those authorized to work in the U.S. are encouraged to apply.
Tax Terms: W2, 1099
Corp-Corp or 3rd Parties: Yes

 

Role: Snowflake Data Engineer

Location: Remote

Client: Kimberly Clark

 

Job Description

  • At least 8 years of IT experience and 4 years or more of work experience in data management disciplines including data integration, modeling, optimization and data quality.
  • Strong experience with advanced analytics tools for Object-oriented/object function scripting using languages such as [R, Python, Java, C++, Scala, others].
  • Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.
  • Strong experience with popular database programming languages including [SQL, Blob Storage and SAP HANA] for relational databases and certifications on upcoming [MS Snowflake HDInsights, Cosmos] for non-relational databases.
  • Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. These should include [ETL/ELT, data replication/CDC, message-oriented data movement, API design and access] and upcoming data ingestion and integration technologies such as [stream data integration, CEP and data virtualization].
  • Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production.
  • Strong experience in streaming and message queuing technologies [such Snowflake Service Bus, and Kafka].
  • Basic experience working with popular data discovery, analytics and BI software tools like [Tableau, Power BI and others] for semantic-layer-based data discovery.
  • Strong experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms.
  • Demonstrated success in working with large, heterogeneous datasets to extract business value using popular data preparation tools.
  • Demonstrated ability to work across multiple deployment environments including [cloud, on-premises and hybrid], multiple operating systems and through containerization techniques such as [Docker, Kubernetes].
  • Interpersonal Skills and Characteristics
  • Strong leadership, partnership and communication skills
  • Ability to coordinate with all levels of the firm to design and deliver technical solutions to business problems
  • Ability to influence without authority
  • Prioritization and time management
  • Data modelling with Enterprise Data Warehouse and DataMart, Snowflake Data Lake Gen2 & BLOB.,
  • Data engineering experience with Snowflake Databricks
  • Hands-on experience in SQL, Python, NoSQL, JSON, XML, SSL, RESTful APIs, and other formats of data viz parquet, ORC, AVRO
  • Hands-on emphasis with a proven track record of building and evaluating data pipelines, and delivering systems for final production
  • Exposure to Big Data Analytics (data and technologies), in-memory data processing using spark.
  • Working Experience with various data bases like SAP HANA, Cassandra, Mangodb
  • Strong understanding DevOps, on-premise, and cloud deployments

Roles and responsibilities:

 

  • Build Data Pipelines
  • Drive Automation through effective metadata management
  • Learning and applying modern data preparation, integration and AI-enabled metadata management tools and techniques.
  • Tracking data consumption patterns.
  • Performing intelligent sampling and caching.
  • Monitoring schema changes.
  • Recommending — or sometimes even automating — existing and future integration flows.
  • Collaborate across departments
  • train counterparts in these data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases.
  • Participate in ensuring compliance and governance during data use

Required profile

Experience

Level of experience: Senior (5-10 years)
Industry :
Information Technology & Services
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Time Management
  • Prioritization
  • Communication
  • Leadership

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