76 to 100 of 304 Permanent BigQuery Jobs

Kafka, Apache Spark, Apache Flink, object, relational and NoSQL data stores. Hands-on experience with big data application development and cloud data warehousing (e.g. Hadoop, Spark, Redshift, Snowflake, GCP BigQuery) Expertise in building data architectures that support batch and streaming paradigms Experience with standards such as JSON, XML, YAML, Avro, Parquet Strong communication skills Open to learning new technologies More ❯

tooling, guidance, and best practices. About You: Strong technical foundation in data governance architecture and tooling. You've worked with tools such as DataHub, Apache Airflow, AWS, dbt, Snowflake, BigQuery , or similar. Hands-on experience building and maintaining centralized data inventories, business glossaries, and data mapping frameworks. Proficient in automating data classification and lineage using scripting languages like Python More ❯

motivated, proactive, and able to work independently. Communication Skills: Excellent verbal, written and presentation skills. Educated to a degree level or with demonstrable relevant experience Previous experience working with BigQuery is advantageous. Minimum 3 years' experience of Power BI essential (Dashboard creation, Data Modelling, DAX, Power Query) Understanding of analysis methodologies essential. Previous experience with report building tools is More ❯

motivated, proactive, and able to work independently. Communication Skills: Excellent verbal, written and presentation skills. Educated to a degree level or with demonstrable relevant experience Previous experience working with BigQuery is advantageous. Minimum 3 years experience of Power BI essential (Dashboard creation, Data Modelling, DAX, Power Query) Understanding of analysis methodologies essential. Previous experience with report building tools is More ❯

and Build: Design and implement a robust, cloud-native data analytics platform spanning AWS, GCP, and other emerging cloud environments. You'll leverage services like S3/GCS, Glue, BigQuery, Pub/Sub, SQS/SNS, MWAA/Composer, and more to create a seamless data experience. (Required) Data Lake , Data Zone, Data Governance: Design, build, and manage data More ❯

frontend engineering skills, especially in Python and JavaScript/TypeScript-based environments. Deep knowledge of data modeling, querying (SQL), and connecting analytics platforms to modern data warehouses (e.g., Snowflake, BigQuery ). Experience with authentication/authorization integration, multi-tenancy, and performance tuning in analytics applications. Cloud experience (AWS, Azure, or GCP) and familiarity with containerized deployments (Docker, Kubernetes). More ❯

processes and data quality To be successful in the role you will have: Experience in an analytical role Strong SQL skills for data extraction and manipulation Experience with Google BigQuery is beneficial Proven experience in financial modelling and forecasting Experience using data visualisation tools such as Power BI, Tableau, or Google Looker This is a fully on-site position More ❯

the team. Required skills and experience: Advanced Google Standard SQL and MySQL or similar relational database language Fluency in Python and its application in data analysis Familiarity with Google BigQuery or other data warehouse solution Experience with Tableau; creating & managing data sources and converting complex insights into a digestible format Working knowledge of Google Analytics or other web-based More ❯

impact of business changes, new product launches, pricing strategies and market shifts, and creating comprehensive financial reports and visualisations using Looker. You'll be working with data from Google BigQuery, though prior experience with this is not required, as long as you bring SQL skills for data extraction and manipulation, and a desire to learn how to work with More ❯

impact of business changes, new product launches, pricing strategies and market shifts, and creating comprehensive financial reports and visualisations using Looker. You'll be working with data from Google BigQuery, though prior experience with this is not required, as long as you bring SQL skills for data extraction and manipulation, and a desire to learn how to work with More ❯

impact of business changes, new product launches, pricing strategies and market shifts, and creating comprehensive financial reports and visualisations using Looker. You'll be working with data from Google BigQuery, though prior experience with this is not required, as long as you bring SQL skills for data extraction and manipulation, and a desire to learn how to work with More ❯

with strong analytical thinking, business acumen, and a passion for continuous improvement. Knowledge of ERP systems like Agresso or Oracle Financials is a bonus. Familiarity with tools like Google BigQuery , Looker , DBT , GitHub , Tableau , or Qlik is helpful but not essential. More ❯

What We’re Looking For Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses (BigQuery, Snowflake, Redshift). Proven experience in deploying machine learning models or optimisation algorithms into production. Solid understanding of digital marketing concepts, platforms (e.g., Google Ads, Meta), and analytics tools. More ❯

strategies to continuously enhance the company's data capabilities. YOUR SKILLS AND EXPERIENCE: The ideal Head of Data Platform will have: Extensive experience with Google Cloud Platform (GCP), particularly BigQuery Proficiency with a modern data tech stack, including SQL, Python, Airflow, dbt, Dataform, Terraform Experience in a mid-large sized company within a regulated industry, with a strong understanding More ❯

will have the following skills and experience: Strong hands-on background in data engineering, with 5+ years working on modern data platforms Experience leading cloud data migrations- GCP and BigQuery strongly preferred Proficiency in SQL, Python, dbt, Airflow, Terraform and other modern tooling Excellent understanding of data architecture, governance, and DevOps best practices Proven leadership or team management experience More ❯

Proficiency in the following preferred programming and data environments: Languages: SQL, and/or R or Python Tools: Git, Docker, dbt, MLflow, POSIT Supported IDEs, cloud notebooks Data platforms: BigQuery, Databricks Familiarity with cloud infrastructure and deployment practices (e.g., AWS/GCP/Azure), MLOps pipelines, and containerization. Experience with Bayesian/Probabilistic modeling frameworks (e.g., PyMC, Stan) is More ❯

Statistics, Data Analytics, Computer Science) Experience in data analysis tools (e.g., SQL, Python, etc) Ability to work effectively in a team environment Responsibilities Collect, clean, and optimize datasets in BigQuery or other SQL databases for analysis and reporting Use SQL to query large datasets and uncover trends that support business decisions Design, build, and maintain Looker dashboards, including custom More ❯

maintaining production data systems. Advanced SQL skills and deep experience implementing complex business logic and performance-optimized transformations at scale. Expertise with modern cloud-based data platforms (e.g., Snowflake, BigQuery, Redshift) and experience managing large, distributed data environments. Strong understanding of data architecture and dimensional modeling principles, with a track record of designing enterprise-grade schemas. Proven ability to More ❯

automating models and advancing our engineering practices. You're familiar with cloud technologies . You have experience working with data in a cloud data warehouse (Redshift, Snowflake, Databricks, or BigQuery) Experience with a modern data modeling technology (DBT) You document and communicate clearly . Some experience with technical content writing would be a plus You are excited to work More ❯

SQL, .NET, dbt, Airflow and cloud-native data tools (AWS, GCP or Azure) You have strong knowledge of data architecture patterns - including Lakehouse and modern warehouse design (e.g. Snowflake, BigQuery, Databricks) You know how to build with performance, security and maintainability in mind You can comfortably influence and guide both technical and non-technical stakeholders You're passionate about More ❯

Design and iterate on core product metrics ( user activation, retention, engagement, and monetisation ), ensuring they are accurate, timely, and reliable Build and maintain lightweight, test-covered ELT pipelines (Fivetran BigQuery dbt Hex) that make clean data accessible to everyone Prototype analyses in SQL/Python, starting with the simplest approach and layering complexity only when it materially sharpens the More ❯

in cloud-based data platforms and infrastructure (e.g., AWS, GCP), ensuring scalability and security for large volumes of streaming and batch data. Additionally, experience with data warehouses such as BigQuery or Snowflake. Adept in Python and/or Java for developing data services and integrating APIs to bring in diverse sources of media data. Excellent interpersonal and communication skills … and Infrastructure Building: Build and manage the infrastructure necessary for optimal ETL or ELT of data using Python, SQL, and Google Cloud Platform (GCP) big data technologies, such as BigQuery, Dataflow, Dataproc and Cloud Storage. Business Intelligence Enablement: Prepare and transform pipeline data to support downstream analytics and feed BI tools (DOMO), enabling data-driven decision-making across the … SQL and Database Expertise: Strong working knowledge of SQL with hands-on experience querying and managing relational databases, alongside familiarity with a variety of database technologies (e.g., PostgreSQL, MySQL, BigQuery). Big Data Engineering: Proven experience designing, building, and optimizing ‘big data’ pipelines, architectures, and datasets, enabling efficient data processing at scale. Analytical Problem Solving: Skilled in performing root More ❯

in cloud-based data platforms and infrastructure (e.g., AWS, GCP), ensuring scalability and security for large volumes of streaming and batch data. Additionally, experience with data warehouses such as BigQuery or Snowflake. Adept in Python and/or Java for developing data services and integrating APIs to bring in diverse sources of media data. Excellent interpersonal and communication skills … and Infrastructure Building: Build and manage the infrastructure necessary for optimal ETL or ELT of data using Python, SQL, and Google Cloud Platform (GCP) big data technologies, such as BigQuery, Dataflow, Dataproc and Cloud Storage. Business Intelligence Enablement: Prepare and transform pipeline data to support downstream analytics and feed BI tools (DOMO), enabling data-driven decision-making across the … SQL and Database Expertise: Strong working knowledge of SQL with hands-on experience querying and managing relational databases, alongside familiarity with a variety of database technologies (e.g., PostgreSQL, MySQL, BigQuery). Big Data Engineering: Proven experience designing, building, and optimizing ‘big data’ pipelines, architectures, and datasets, enabling efficient data processing at scale. Analytical Problem Solving: Skilled in performing root More ❯

in a financial or analytical role. Degree (or equivalent experience) in Finance, Economics, Accounting or a numerate discipline (preferred). Proficient in SQL for data analysis; experience with Google BigQuery is advantageous. Strong experience in building financial models and conducting forecasting. Excellent analytical, mathematical and problem-solving abilities. Proficiency in data visualisation tools such as Google Looker, Tableau or More ❯

ll be given the space to lead your domain, backed by support and guidance when needed, but never micromanaged. What You’ll Bring Solid technical foundation, especially in SQL , BigQuery , and data pipelines . A curious mindset with the ability to translate messy data into clean insight — ideally from a background in marketing analytics , Data Science or MarTech . More ❯