pipelines. Work with Python and SQL for data processing, transformation, and analysis. Leverage a wide range of GCP services including: Cloud Composer (Apache Airflow) BigQuery Cloud Storage Dataflow Pub/Sub Cloud Functions IAM Design and implement data models and ETL processes. Apply infrastructure-as-code practices using tools More ❯
But if not? We’ll help you get there: Understanding of cloud computing security concepts Experience in relational cloud-based database technologies like Snowflake, BigQuery or Redshift Experience in open-source technologies like Spark, Kafka, Beam understanding of Cloud tools such as AWS, Microsoft Azure or Google Cloud Familiarity More ❯
in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra). • In-depth knowledge of data warehousing concepts and tools (e.g., Redshift, Snowflake, GoogleBigQuery). • Experience with big data platforms (e.g., Hadoop, Spark, Kafka). • Familiarity with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud More ❯
/ELT pipelines and database technologies like PostgreSQL and MongoDB Familiar with major cloud platforms and tools, ideally Amazon Web Services and Snowflake or BigQuery Solid understanding of data transformation, advanced analytics, and API-based data delivery Ability to work across departments with a collaborative, problem-solving mindset and More ❯
data engineering, with a strong focus on Google Cloud Platform (GCP)-based solutions. Proficiency in the GCP platform, particularly in Data & AI services (e.g., BigQuery, DataProc, Cloud SQL, DataFlow, Pub/Sub, Cloud Data Fusion, Cloud Composer, Python, SQL). Designing, developing, and deploying scalable, reliable, and secure cloud More ❯
Cambridge, Cambridgeshire, UK Hybrid / WFH Options
Intellect Group
client-facing environment Familiarity with tools and frameworks such as: Databricks PySpark Pandas Airflow or dbt Experience deploying solutions using cloud-native services (e.g., BigQuery, AWS Glue, S3, Lambda) What’s On Offer Fully remote working with the flexibility to work from anywhere in the UK Optional weekly in More ❯
customer segmentation, forecasting, and LTV analysis • Maintain code-driven workflows and version control through GitHub What We’re Looking For: • Strong SQL skills (GoogleBigQuery or similar cloud platforms) • Proficiency in Tableau or other data visualisation tools • Understanding of data modelling (Kimball methodology preferred) • Experience with DBT/Airflow More ❯
is a plus). Experience with Airflow or similar orchestration tools. Familiarity with MLflow or MLOps practices. Knowledge of data warehousing solutions (Snowflake, Redshift, BigQuery). Consulting background is a plus. Strong communication skills (oral & written) Rights to work in the UK is must (No Sponsorship available) Responsibilities: Design More ❯
fostering a positive and inclusive team culture What we’re looking for: Hands-on experience building and maintaining cloud-based data systems (e.g., Redshift, BigQuery, Snowflake) Strong coding skills in languages commonly used for data work (e.g., Python, Java, Scala) Deep understanding of ETL/ELT tools and workflow More ❯
commercial environment creating production grade ETL and ELT pipelines in python Comfortable implementing data architectures in analytical data warehouses such as Snowflake, Redshift or BigQuery Hands on experience with data orchestrators such as Airflow Knowledge of Agile development methodologies Awareness of cloud technology particularly AWS. Knowledge of automated delivery More ❯
star schemas and de-normalised structures Required Skills & Experience: Strong experience using data modelling tools Hands-on experience with Google Cloud technologies such as BigQuery, GCS, and Kafka Advanced SQL skills and experience with ETL tools (e.g., SSIS), scripting in Python and Unix Shell Familiarity with Agile methodologies Strong More ❯
familiar with the auditing process to verify the efficacy of the data being captured. Naturally you’ll be comfortable working with SQL and ideally BigQuery (though a similar data warehousing technology is fine) with PowerBI experience being a big bonus, though by no means essential. Bonus points if you More ❯
and mobile app development, SQL, ETL or data pipelines, and data analysis. You have experience with cloud data warehouses/lakes including Snowflake, Databricks, BigQuery, Redshift, S3, and ADLS. You have experience with AWS, GCP, and/or Azure cloud services. You have strong technical skills and experience with More ❯
expect to get involved in a variety of projects in the cloud (AWS, Azure, GCP), while also gaining opportunities to work with Snowflake, Databricks, BigQuery, and Fabric. We work with near real-time/streaming data, geospatial data and using modern AI-tooling to accelerate development. About You You More ❯
with Python, SQL, and modern ETL tools (e.g., Airflow, dbt) Solid grasp of cloud platforms (AWS/GCP/Azure) and data warehouses (e.g., BigQuery, Snowflake) Familiarity with streaming technologies (Kafka, Kinesis, etc.) Passion for clean, maintainable code and robust data systems Previous experience in a fintech or regulated More ❯
external clients. Strong hands-on experience using SQL for multi-step/complex analytics is essential for this role. Experience in cloud platforms (GCP – BigQuery, Azure -Synapse, Snowflake) and exposure to data science tools/languages such as Python, dbt, D3, Github, GCP/AWS would be advantageous. (This More ❯
insights and automation Working knowledge of database technologies (relational, columnar, NoSQL), e.g., MySQL, Oracle, MongoDB Experience with modern cloud data warehouses (e.g., Snowflake, Databricks, BigQuery) Excellent organisational and multitasking skills across multiple sales cycles Agile and adaptable to evolving customer needs and priorities Creative problem-solver with a strategic More ❯
POV/POCs, configuring a cloud storage bucket for a customer to upload sample data to, configuring cloud permissions to access a customer’s BigQuery instance in order to create a materialized view. What You’ll Need Technical Expertise Comfortable working with APIs (REST, GraphQL). Able to interpret More ❯
insights that matter. You’ll need: Hands-on experience with GA4, Google Analytics 360, Google Tag Manager, and CRM tools. Proficiency in SQL, within BigQuery environment. Strong dashboarding and visualisation skills using Tableau, Looker, or Google Data Studio. A keen eye for detail and a love of structured, reliable More ❯
data integration issues and develop creative solutions. Nice to Have: 1. *Cloud Data Platforms*: Experience with cloud data platforms such as AWS Redshift, GoogleBigQuery, or Azure Synapse Analytics. 2. *Data Science*: Knowledge of data science concepts and experience with data science tools such as R, Julia, or TensorFlow. More ❯
Architect with us? Create Solution architectures for Data Engineering and Analytics projects using google native products like Pub/Sub, DataFlow, Cloud Functions, GoogleBigQuery and Looker Create Solution architectures for Data Engineering and Analytics projects using AWS products like S3, Redshift, QuickSight and AWS SageMaker Build High performance More ❯
Python Experience developing in the cloud (AWS preferred) Solid understanding of libraries like Pandas and NumPy Experience in data warehousing tools like Snowflake, Databricks, BigQuery Familiar with AWS Step Functions, Airflow, Dagster, or other workflow orchestration tools Commercial experience with performant database programming in SQL Capability to solve complex More ❯
at least 2 Cloud platforms (Azure, AWS, GCP, Snowflake, Databricks) and Big Data processing (e.g., Apache Spark, Beam). Proficiency in key technologies like BigQuery, Redshift, Synapse, Pub/Sub, Kinesis, Event Hubs, Kafka, Dataflow, Airflow, and ADF. Strong ETL and data modeling skills. Proven ability to design and More ❯
in SQL, Python, SSIS, and shell scripting Familiarity with data modelling tools like ER/Studio Experience working with Google Cloud Platform components (e.g., BigQuery, GCS, Kafka) Knowledge of agile development practices Comfortable engaging with clients and working collaboratively within cross-functional teams More ❯
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., GoogleMore ❯
