Job Title: Data Engineer/ Data ArchitectLocation: Corvallis, OR – 5 Days Onsite Role Job Description: At least 8 to 10+ years’ experience in data engineering , AI and ML and Aws/Azure Architect, Design and implement distributed data processing pipelines using Spark, Python, SQL and other tools and languages prevalent in the Big Data/Lakehouse ecosystem.

Job Title: Jr. Big Data Engineer (Urgent hiring) We are a premier IT consulting firm specializing in delivering top-tier Big Data solutions to companies across various sectors such as.

The big data architect will support the development of autonomous driving software solutions by playing the role of subject matter expert for the big data systems, underlying data and data products.

Engineering experience in big data environments, including data lakes, Azure Synapse, Databricks, Redshift, Snowflake. Databricks Certified Data Engineer. As a member of the Baseline Analytics Data Engineering team, the Data Engineer Summer Associate will focus on creating new data pipelines that use powerful cloud tools to deliver data and insights to analysts at NFCU.

As a big data engineer at Booz Allen, you'll implement data engineering activities on some of the most mission-driven projects in the industry. We need an experienced data engineer like you to help our clients find answers in their big data to impact important missions—from fraud detection to cancer research to national intelligence.

This role will provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations for the District of Columbia government, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.

As a Senior DevOps engineer, you will play a crucial role in ensuring the ESP software product teams (primarily focused on the Pattern in-house WIS:dom for big data across weather, energy pricing, and geospatial data.

Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. What you'll bring to Circle: For Senior Data Engineer (III) 4+ years of professional data engineering experience.

As a member of the Data Engineering Web3 team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity in our Web3 product offerings. Designing, building and maintaining data ETL/ELT pipelines to source and aggregate the required data for various data analyses and reporting needs, as well as to continually improve the operations, monitoring and performance of the data warehouse.

Familiarity with data privacy standards, methodologies, and best practicesPractical hands-on experience with data technologies and Cloud Platform like Hadoop, Hive, Redshift, Big Query, Snowflake, Databricks, GCP and Azure.

Utilize Databricks for big data processing and streaming analytics. Experience with big data technologies such as Apache Hadoop, Spark, Kafka, and others. The ideal candidate will have a robust background in big data analytics, data engineering, and cloud computing, with a particular focus on building and optimizing data lakes on AWS. This role is crucial for designing, implementing, and managing advanced data solutions using AWS and Data Lakehouse platforms.

YOUR SKILLS AND EXPERTISEBachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.STANDOUT QUALIFICATIONS:Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query)Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.

Experience of implementing Amazon EMR or Big Data technologies like Hadoop, Spark, Presto, Hive will be a plus Prior domain experience of Life Insurance, Annuity or Financial Services is a plus AWS Certifications are considered a strong plus Excellent verbal and written communication skills.

Plant monitoring and care during vegetative and flowering phase: trimming and staking; big leafing and pruning; plant care, watering and feeding; plant monitoring and climate control; pest and disease control; inventory data input.

Exposure to big data platforms - Snowflake, Redshift, Azure, Matillion, Hadoop. You have a strong background in data quality management and are experienced with SaaS and/or digital sales metrics.