1 to 25 of 416 BigQuery Jobs

services for data engineering. Experience with Azure Key Vault, Azure Monitor, and RBAC. AWS: Experience with S3, Glue, Redshift, and Lambda. Familiarity with IAM, CloudWatch, and Athena. Experience with BigQuery, Cloud Storage, and Dataflow. Familiarity with Cloud Functions, IAM, and Vertex AI (optional). Experience in one or more of the following Data Platforms: Microsoft: Experience with Azure Data More ❯

understanding of data architecture, schema design, normalization/denormalization, and data lifecycle management Cloud data platforms: Azure Data Services (preferred), AWS, or Google Cloud Platform Data Warehousing: Synapse, Snowflake, BigQuery, Redshift, etc. Proficient in Reporting Platforms to query large data sets Ex: PowerBI, Tableau, Looker, or similar tools Familiarity with data governance security, and compliance best practices (Collibra, Unity More ❯

role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field ● Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Redshift, BigQuery or other big data solutions ● Experience in data modelling and tools such as dbt, ETL processes, and data warehousing ● Experience with at least one of the programming languages like More ❯

role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field ● Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Redshift, BigQuery or other big data solutions ● Experience in data modelling and tools such as dbt, ETL processes, and data warehousing ● Experience with at least one of the programming languages like More ❯

to cloud 2+ years of experience leading and delivering complex cloud architecture engagements across distributed teams Hands-on experience with big data tools (Spark, Redshift, Snowflake, Azure SQL DW, BigQuery) Experience with BI/reporting tools (Power BI, Tableau, Looker, etc.) Strong SQL and proficiency in Python, Java, or C# Familiarity with data warehousing concepts (SCD, Star Schema, etc. More ❯

actionable insights for various departments. Required Qualifications Technical Skills - Programming & Query Languages: Strong proficiency in Python, SQL, and PySpark. - Big Data Platforms: Experience with cloud data platforms including Snowflake, BigQuery, and Databricks. Databricks experience highly preferred. - Orchestration Tools: Proven experience with workflow orchestration tools (Airflow preferred). - Cloud Platforms: Experience with AWS (preferred), Azure, or Google Cloud Platform. - Data More ❯

expertise in Data Warehouse design and Dimensional Modeling 5+ years of professional experience working with cloud or on-premises Big Data/MPP analytics platform (Teradata, AWS Redshift, Google BigQuery, Azure Synapse Analytics, or similar) Experience with data quality and validation (using Apache Airflow) Experience with anomaly/outlier detection Experience with Data Science workflow (Jupyter Notebooks, Bento, or More ❯

scalable data pipelines and data models; Strong programming skills in SQL; Experience with cloud platforms such as AWS, GCP, or Azure, and their respective data services (e.g., S3, Redshift, BigQuery); Experience with data visualization tools such as Tableau, Looker, or Power BI; Strong problem-solving and analytical skills, with experience in statistical modeling; Excellent communication skills and ability to More ❯

RStudio/Posit, is a plus but not a requirement Experience with data orchestration and workflow management (e.g., Airflow, dbt, or similar) Knowledge of cloud data platforms (Snowflake, Redshift, BigQuery, Databricks, or similar), with the ability to guide evaluation, adoption, and integration Strong grasp of data governance, quality control, security, and monitoring practices A mindset of partnership-comfortable explaining More ❯

experience in Python development for data workflows Experience building and maintaining ETL pipelines, ideally with Apache Airflow or a similar orchestration tool Hands-on experience with Google Cloud Platform (BigQuery, GCS, etc.) or another major cloud provider Good understanding of data modelling principles and the ability to translate business needs into technical solutions Strong collaboration and communication skills, with More ❯

tests, marketing campaigns and product workflows. Communication - Present findings, work product, and recommendations to both technical and non-technical stakeholders Systems - Work with cloud-based data warehouses (e.g., Snowflake, BigQuery, Redshift) and analytics tools (e.g., dbt, Sigma, Looker, Tableau) in addition to standing up a data science tool stack Minimum Qualifications: 3-5+ years of experience in data More ❯

years of experience in data engineering or analytics, including designing and delivering enterprise grade data solutions Strong hands-on experience with Snowflake (or comparable cloud data warehouses like BigQuery, RedShift, Synapse) including data modelling, performance tuning and cost management Familiarity with SQL best practices, ELT patterns, and modern data transformation frameworks such as dbt Competence in at least one More ❯

years of experience in data engineering or analytics, including designing and delivering enterprise grade data solutions Strong hands-on experience with Snowflake (or comparable cloud data warehouses like BigQuery, RedShift, Synapse) including data modelling, performance tuning and cost management Familiarity with SQL best practices, ELT patterns, and modern data transformation frameworks such as dbt Competence in at least one More ❯

big data platforms. Knowledge of data modeling, replication, and query optimization. Hands-on experience with SQL and NoSQL databases is desirable. Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: Comfortable operating in hybrid environments (cloud and on-prem). Experience integrating diverse data sources and systems. Understanding of secure data transfer protocols More ❯

decisions and optimize the growth funnel What You Bring 3-5 years of experience in data analytics or data science. Advanced SQL proficiency and experience working with modern databases (BigQuery, Snowflake, Redshift) Experience building dashboards with data visualization tools (Looker, Tableau, Power BI). Demonstrated track record of success in a high-growth, self-directed business environment. Strong analytical More ❯

e.g., AWS, Azure, Google Cloud Platform). Strong problem-solving and analytical skills. Excellent communication and teamwork abilities. Preferred Skills: Experience with data warehousing solutions (e.g., Amazon Redshift, Google BigQuery). Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). Knowledge of data governance and data privacy regulations. Certification in data engineering or related fields. More ❯

e.g., SQL, R). Experience with data processing frameworks (e.g., Apache Spark, Hadoop) and orchestration tools (e.g., Airflow). Familiarity with cloud-based data solutions (e.g., AWS Redshift, Google BigQuery, Azure Data Factory). Proven experience in data modeling, database design, and data architecture frameworks. Strong analytical and problem-solving skills, with attention to detail. Excellent communication and collaboration More ❯

frameworks (e.g., Spark, Flink, Hadoop) and workflow orchestration (Airflow, Prefect, Dagster). Proven experience with cloud-based data platforms (AWS, GCP, Azure) and data lake/warehouse technologies (Snowflake, BigQuery, Redshift, Delta Lake). Strong understanding of data modeling, ETL/ELT processes, and distributed data systems. Experience with streaming data systems (Kafka, Kinesis, Pub/Sub) preferred. Knowledge More ❯

data tools and governance. Strong analytical mindset with a focus on business outcomes. Nice-to-Have Python or Airflow experience for automation. Knowledge of data warehouse best practices (Snowflake, BigQuery, Redshift). Experience with MS Business Central or similar ERP systems. eCommerce or omni-channel retail background. Exposure to machine learning and predictive analytics. This is a great opportunity More ❯

and compatibility with model requirements. Deep understanding of transformer architectures, reinforcement learning, and sequential decision-making models. Strong command of SQL and data modeling in cloud warehouses (e.g., Snowflake, BigQuery, Redshift). Worked with Agile development environment, participating in sprints, stand-ups, and iterative project cycles to deliver high-quality data-driven solutions. Develop and maintain production-level code More ❯

Experience cloud-based data warehousing and data lake solutions like Snowflake, Redshift, Databricks 5+ years of experience with SQL or NoSQL database (PostgreSQL, MySQL, SQL server, Oracle, Aurora, Presto, BigQuery) Expertise with SQL, database design/structure and data structure (star, snowflake schemas, de/normalized designs) 5+ years of experience with at least one programming language (Python, Java More ❯

Science, Engineering, or a related field. 5+ years of experience in data engineering or a related field. Strong proficiency in SQL and database technologies with (e.g., PostgreSQL, MySQL, Snowflake, BigQuery). Experience with data pipeline orchestration tools (e.g., Apache Airflow, Prefect, Dagster). Proficiency in programming languages such as Python and Scala. Hands-on experience with AWS cloud data More ❯

Java, strong SQL skills, and knowledge of big data tools like Apache Hadoop, Spark, or Kafka. Experience with cloud platforms (AWS, Azure, GCP) and data warehousing solutions (Snowflake, Redshift, BigQuery) Self-driven and have demonstrated the ability to work independently with minimum guidance Demonstrated multitasking ability, problem solving skills and a consistent record of on time delivery and customer More ❯

required reports. Ensure data consistency, governance, and alignment of key metrics across the organization. Write efficient SQL queries to extract, transform, and analyze large datasets from data warehouses (e.g., BigQuery). Develop clean, intuitive dashboards and visualizations that make complex data accessible to stakeholders. Communicate findings clearly to both technical and non-technical audiences, turning data into narratives that More ❯

optimize SQL views, Python/R scripts, and API connectors as needed. Continually optimize data cleaning and anomaly detection processes. Help manage and advance our GCP infrastructure, particularly with BigQuery and GCP integrations. Own data quality and governance Enforce naming conventions, dataset groupings, versioning, and access standards. Maintain rigorous QA practices to ensure clean, reliable, and consistent data. Continuously More ❯