Our values are Trust, Efficiency, and Drive. What will I be doing? Design, build, and maintain scalable and reliable data pipelines. Manage Zeelo’s serverless centralized data architecture (Fivetran, BigQuery, dbt, and other tools) that supports analytical functions across the business. Design, build, and maintain ETL, ELT and other data pipelines for purposes to support analytics use cases. Identify More ❯
familiarity with data warehousing, data lake/lakehouse architectures, and cloud-native analytics platforms. Hands-on experience with SQL and cloud data platforms (e.g., Snowflake, Azure, AWS Redshift, GCP BigQuery). Experience with BI/analytics tools (e.g., Power BI, Tableau) and data visualization best practices. Strong knowledge of data governance, data privacy, and compliance frameworks (e.g., GDPR, ISO More ❯
familiarity with data warehousing, data lake/lakehouse architectures, and cloud-native analytics platforms Hands-on experience with SQL and cloud data platforms (e.g., Snowflake, Azure, AWS Redshift, GCP BigQuery) Experience with BI/analytics tools (e.g., Power BI, Tableau) and data visualization best practices Strong knowledge of data governance, data privacy, and compliance frameworks (e.g., GDPR, ISO More ❯
THE COMPANY: At Fit Collective , we’re solving one of the fashion industry’s biggest - and most expensive - problems: poor fit. It's the leading cause of returns, responsible for nearly $1 trillion in lost revenue , 4 billion pounds of More ❯
Job Description Data Architect Data Architects at Next work closely with the Next Architect teams to identify potential technology innovations, make recommendations that support business growth and drive efficiencies, align business requirements with Next strategy, and are responsible for designing More ❯
and data AI Agents. You will be designing and proposing effective combinations of Google Marketing Platform tools (GA4, Campaign Manager 360, Search Ads 360, etc.) and Google Cloud solutions (BigQuery, BQ Sharing (Analytics Hub), Cloud Storage, APIs, Compute Engine, etc.) to address specific client needs. You will be designing, maintaining, and optimising data infrastructure for data collection, management, transformation … Experience with creating AI Agents. Develop and maintain efficient data pipelines, ETL processes, and data warehousing solutions. Proficiency in Python and SQL. Demonstrable expertise in Google Cloud Platform (e.g., BigQuery, BQ Sharing (Analytics Hub), Cloud Functions, Dataflow, Looker Studio) to build scalable and secure data solutions. Other cloud-based technologies such as Windows Azure, AWS are desirable. Hands-on More ❯
and data AI Agents. You will be designing and proposing effective combinations of Google Marketing Platform tools (GA4, Campaign Manager 360, Search Ads 360, etc.) and Google Cloud solutions (BigQuery, BQ Sharing (Analytics Hub), Cloud Storage, APIs, Compute Engine, etc.) to address specific client needs. You will be designing, maintaining, and optimising data infrastructure for data collection, management, transformation … Experience with creating AI Agents. Develop and maintain efficient data pipelines, ETL processes, and data warehousing solutions. Proficiency in Python and SQL. Demonstrable expertise in Google Cloud Platform (e.g., BigQuery, BQ Sharing (Analytics Hub), Cloud Functions, Dataflow, Looker Studio) to build scalable and secure data solutions. Other cloud-based technologies such as Windows Azure, AWS are desirable. Hands-on More ❯
London, England, United Kingdom Hybrid / WFH Options
Derisk360
sources. Design and implement advanced Graph Database solutions using Neo4j, Cypher queries, and GCP-native integrations. Create ETL/ELT workflows leveraging GCP services including Dataflow, Pub/Sub, BigQuery, and Cloud Storage. Model real-world use cases in Neo4j such as fraud detection, knowledge graphs, and network analysis. Optimize graph database performance, ensure query scalability, and maintain system … years of experience in data engineering, including 2+ years with Neo4j or another Graph DB platform. Proficiency in SQL, Python, and Cypher query language. Strong hands-on experience with BigQuery, Dataflow, Pub/Sub, and Cloud Storage. Expertise in graph theory, graph schema modeling, and data relationship mapping. Bachelor’s degree in Computer Science, Engineering, or a related field. More ❯
more junior members of staff. Required Skills & Experience: Proven experience as a Data Engineer in a commercial environment. Strong hands-on experience with Google Cloud Platform (GCP) services (e.g., BigQuery, Dataflow, Pub/Sub). Solid understanding of Azure data services and hybrid cloud environments. Advanced SQL skills and proficiency in Python for data engineering tasks. Experience working in More ❯
more junior members of staff. Required Skills & Experience: * Proven experience as a Data Engineer in a commercial environment. * Strong hands-on experience with Google Cloud Platform (GCP) services (e.g., BigQuery, Dataflow, Pub/Sub). * Solid understanding of Azure data services and hybrid cloud environments. * Advanced SQL skills and proficiency in Python for data engineering tasks. * Experience working in More ❯
SaaS or tech environment, but this isn't set in stone! Familiarity with digital advertising platforms (Google Ads, Facebook Ads, LinkedIn Ads, TikTok, etc.) We use Google Analytics 4, BigQuery, Fivetran, Amplitude, Metabase and DBT amongst other things for our data stack, so experience here would be beneficial, however, experience in similar tools (if not these ones) is a More ❯
Experience with big data technologies (Spark, Hadoop, Kafka) is a plus. Hands-on experience with cloud platforms (AWS, Azure, Google Cloud). Knowledge of ETL tools, data warehouses (Snowflake, BigQuery, Redshift) and pipeline orchestration (Airflow, dbt). Understanding of data modeling, database design, and data governance principles . Familiarity with CI/CD pipelines for data workflows is a More ❯
used backend programming languages (Python, Node.JS, Java, PHP, GO, C#, C++) Familiar with version control tools and proper branching techniques (Gitlab preferred) Experience working with data warehouses (Google Cloud BigQuery), data governance, payments and treasury or capital markets systems So, what's in it for you? Our people are constantly striving to be the best through operational excellence. The More ❯
management practices, system development life cycle management, IT services management, agile and lean methodologies, infrastructure and operations, and EA and ITIL frameworks. Proficiency with data warehousing solutions (e.g., GoogleBigQuery, Snowflake). Expertise in data modeling tools and techniques (e.g., SAP PowerDesigner, EA Sparx). Strong knowledge of SQL and NoSQL databases (e.g., MongoDB, Cassandra). Familiarity with cloud More ❯
used backend programming languages (Python, Node.JS, Java, PHP, GO, C#, C++) Familiar with version control tools and proper branching techniques (Gitlab preferred) Experience working with data warehouses (Google Cloud BigQuery), data governance, payments and treasury or capital markets systems So, what's in it for you? Our people are constantly striving to be the best through operational excellence. The More ❯
engage technical and non-technical stakeholders alike. The Head of BI will work within a modern, cloud-based BI ecosystem, including: Data Integration: Fivetran, HVR, Databricks, Apache Kafka, GoogleBigQuery, Google Analytics 4 Data Lake & Storage: Databricks Delta Lake, Amazon S3 Data Transformation: dbt Cloud Data Warehouse: Snowflake Analytics & Reporting: Power BI, Excel, Snowflake SQL REST API Advanced Analytics More ❯
and non-technical stakeholders alike. The Head of Data Engineering & Insight will work within a modern, cloud-based BI ecosystem , including: Data Integration: Fivetran , HVR, Databricks , Apache Kafka, GoogleBigQuery , Google Analytics 4 Data Lake & Storage: Databricks Delta Lake, Amazon S3 Data Transformation: dbt Cloud Data Warehouse: Snowflake Analytics & Reporting: Power BI, Excel, Snowflake SQL REST API Advanced Analytics More ❯
Understanding of statistical methods for analysing operational efficiency, customer behaviour, cohort analysis, and predictive modelling for business metrics GCP Familiarity: Working knowledge of Google Cloud Platform analytics tools, particularly BigQuery for large-scale data analysis Problem Solving & Communication: Proven ability to translate complex operational questions into analytical frameworks and communicate findings effectively to stakeholders at all levels Responsibilities Cross More ❯
and non-technical stakeholders alike. The Head of Data Engineering & Insight will work within a modern, cloud-based BI ecosystem , including: Data Integration: Fivetran , HVR, Databricks , Apache Kafka, GoogleBigQuery , Google Analytics 4 Data Lake & Storage: Databricks Delta Lake, Amazon S3 Data Transformation: dbt Cloud Data Warehouse: Snowflake Analytics & Reporting: Power BI, Excel, Snowflake SQL REST API Advanced Analytics More ❯
similar scripting languages for data science Experience with data processes and building ETL pipelines Experience with cloud data warehouses such as Snowflake, Azure Data Warehouse, Amazon Redshift, or GoogleBigQuery Proficiency in creating visualizations using Power BI or Tableau Experience designing ETL/ELT solutions with tools like SSIS, Alteryx, AWS Glue, Databricks, IBM DataStage Strong analytical and technical More ❯
Azure Synapse Azure SQL Azure DataBricks Microsoft Fabric Azure data lake Exposure to other data engineering and storage tools: Snowflake AWS tools - Kinesis/Glue/Redshift Google tools - BigQuery/Looker Experience working with open datasets - ingesting data/building API based queries Our benefits Here at North Northamptonshire Council, we're transforming for the better, using all More ❯
Senior Data Engineer London (Hybrid) We are Manufacturing the Future! Geomiq is revolutionizing traditional manufacturing by providing engineers worldwide with instant access to reliable production methods through our digital platform. As the UK's leading Digital Manufacturing Marketplace, we offer More ❯
Experience as a Data Product Owner or Product Owner for data/analytics platforms. Experience managing data products or platforms, ideally customer data platforms (CDPs), data warehouses (e.g. Snowflake, BigQuery), or data lakes. Familiarity with data engineering workflows, data tools (dbt, Airflow), and cloud data platforms (AWS, GCP, Azure). Familiarity with data modelling, data pipelines, ETL/ELT More ❯
Experience as a Data Product Owner or Product Owner for data/analytics platforms. Experience managing data products or platforms, ideally customer data platforms (CDPs), data warehouses (e.g. Snowflake, BigQuery), or data lakes. Familiarity with data engineering workflows, data tools (dbt, Airflow), and cloud data platforms (AWS, GCP, Azure). Familiarity with data modelling, data pipelines, ETL/ELT More ❯
Experience as a Data Product Owner or Product Owner for data/analytics platforms. Experience managing data products or platforms, ideally customer data platforms (CDPs), data warehouses (e.g. Snowflake, BigQuery), or data lakes. Familiarity with data engineering workflows, data tools (dbt, Airflow), and cloud data platforms (AWS, GCP, Azure). Familiarity with data modelling, data pipelines, ETL/ELT More ❯
