1 to 25 of 680 SQL Jobs in Berkshire

Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes and data pipeline architecture Excellent communication skills with the ability to collaborate across cross-functional teams Experience managing client relationships More ❯

years’ experience in data engineering, including technical or team leadership. Expertise in AWS (preferred) or Azure , and experience managing data pipelines in the cloud. Strong skills in Python and SQL , with a solid grasp of data warehousing concepts. Experience with DBT , Redshift , or Postgres , and familiarity with BI tools (Power BI preferred). Proven understanding of CI/CD principles More ❯

Agile delivery by contributing to backlog grooming, sprint planning, and story refinement. Required Skills & Experience: • Strong experience in data analysis, data reconciliation, and data testing. • Hands-on experience with SQL and at least one scripting language (e.g. Python). • Familiarity with relational databases and data warehousing concepts. • Experience working with market data, trading data, or financial reference data. • Exposure to More ❯

engineers and analysts. Candidate Profile Proven experience leading data engineering or BI teams in complex organisations. Expertise in cloud data platforms and data processing services. Strong skills in Python, SQL, and Power BI (DAX, Power Query, data modelling). Knowledge of ETL/ELT pipelines, data warehousing, and data mesh architectures. Familiarity with AI/ML applications, metadata management, and More ❯

and CI/CD pipelines. Key Skills: Proven experience in Python programming for data analysis (pandas, numpy, Jupyter). Strong object-oriented programming and design pattern knowledge. Experience with SQL and relational databases. Familiarity with data visualisation tools (e.g., Plotly Dash, Power BI). Understanding of software development best practices (Git, CI/CD, testing). Exposure to cloud computing More ❯

technical direction and project outcomes. What You’ll Need 4+ years of data engineering experience , including at least 2 years hands-on with modern data platforms. Strong proficiency in SQL , data modelling, and query optimisation. Practical experience with Snowflake, Databricks, AWS Redshift, or Microsoft Fabric . Solid understanding of ETL/ELT pipelines and data warehousing principles . Strong communication More ❯

warehouses in cloud environments. Advanced knowledge of AWS or Azure data services (Databricks, Glue, Redshift, S3 Data Lakes, Spark, or equivalent). Strong programming and data manipulation skills (Python, SQL). Solid background in financial reporting, trading data, or analytics within financial markets. Proven ability to manage complex, end-to-end data projects and collaborate cross-functionally across business units. More ❯

alongside commercial teams. • 5+ years of experience with analytical tools such as Power BI and Azure Data Studio. • Strong data analysis skills with advanced Excel expertise. • Proven experience with SQL and Python. • Ability to translate large datasets into actionable insights. • Strong communication skills, with the ability to present data-driven findings to senior stakeholders. • Proficiency in creating impactful presentations in More ❯

years of experience in data engineering or related roles. Strong expertise in Databricks, Spark, Delta Lake, and cloud data platforms (AWS, Azure, or GCP). Proficiency in Python and SQL for data manipulation and transformation. Experience with ETL/ELT development and orchestration tools (e.g., Apache Airflow, dbt, Prefect). Knowledge of data modelling, data warehousing, and lakehouse architectures. Familiarity More ❯

relevant languages such as Python, JavaScript, or TypeScript. • Data Systems Knowledge: •Exposure to working in data-centric environments, supporting ETL/ELT pipelines or data processing services. •Familiarity with SQL and NoSQL databases. •Understanding of data privacy and security concepts. • Ways of Working: •Comfortable working in Agile/Scrum environments, participating in sprint planning, stand-ups, and retrospectives. •Experience using More ❯

with performance tuning and troubleshooting in complex environments. Data Systems Knowledge: Exposure to working in data-centric environments, supporting ETL/ELT pipelines or data processing services. Familiarity with SQL and NoSQL databases. Understanding of data privacy and security concepts. Tooling & Infrastructure: Experience with CI/CD pipelines, containerization (Docker/Kubernetes), and version control systems (e.g., Git). Ways More ❯

with performance tuning and troubleshooting in complex environments. Data Systems Knowledge: Exposure to working in data-centric environments, supporting ETL/ELT pipelines or data processing services. Familiarity with SQL and NoSQL databases. Understanding of data privacy and security concepts. Tooling & Infrastructure: Experience with CI/CD pipelines, containerization (Docker/Kubernetes), and version control systems (e.g., Git). Ways More ❯

ideally in investment banking or financial services. Solid understanding of trade lifecycle , pricing , and risk management . Familiarity with FIX protocol , MQ messaging , and RESTful APIs . Experience with SQL databases and data modelling. Knowledge of DevOps practices , CI/CD pipelines, and version control tools (e.g., Git). Excellent problem-solving and communication skills. Desirable: Experience with vendor platforms More ❯

client priorities with delivery teams to ensure successful outcomes. Experience & skills you'll bring: 3+ years’ experience as a Data Analyst or Technical Business Analyst within Financial Services. Strong SQL skills for data querying, manipulation, and analysis. Ability to translate complex data into clear insights for technical and non-technical stakeholders. Experience in requirements gathering, documentation, process mapping, and data More ❯

Technology, or a related field. Proven experience with Salesforce Data Cloud and other Salesforce products. Strong understanding of data management concepts, data governance, and data integration methodologies. Proficiency in SQL, data modeling, and analytics tools. Demonstrated expertise in API development and integration. Excellent problem-solving skills and attention to detail. Strong communication and interpersonal skills. Experience in training or mentoring More ❯

a global or large-scale environment. Strong understanding of data governance, data quality, and compliance frameworks (e.g., GDPR, CCPA). Expertise in data analytics tools and technologies, such as SQL, Python, R, Tableau, or similar. Experience with big data technologies and cloud platforms (e.g., AWS, Azure, Google Cloud). Excellent analytical and problem-solving skills, with a strong business acumen. More ❯

Bachelor’s degree in a STEM field (Computer Science, Engineering, Maths, Physics). 2–4 years’ experience in a technical, data, or engineering-focused role. Strong skills in Python, SQL, and Excel/VBA . Experience building or maintaining ETL/data pipelines , particularly around APIs or FTP processes. Working knowledge of Microsoft Azure and Git . Excellent analytical, communication More ❯

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 programming language (Python preferred) for automation. Experience with cloud platforms (AWS, Azure, or More ❯

PySpark - Hands-on experience with AWS services, especially EMR, S3, Lambda, and Glue - Deep understanding of Snowflake architecture and performance tuning - Solid grasp of data modeling, warehousing concepts, and SQL optimization - Familiarity with CI/CD tools (e.g., Jenkins, GitHub Actions) and infrastructure-as-code - Experience with data governance frameworks and security best practices - Excellent communication and collaboration skills Nice More ❯

PySpark - Hands-on experience with AWS services, especially EMR, S3, Lambda, and Glue - Deep understanding of Snowflake architecture and performance tuning - Solid grasp of data modeling, warehousing concepts, and SQL optimization - Familiarity with CI/CD tools (e.g., Jenkins, GitHub Actions) and infrastructure-as-code - Experience with data governance frameworks and security best practices - Excellent communication and collaboration skills Nice More ❯

degree in Computer Science or related STEM field (or equivalent experience). 10+ years of hands-on experience developing with C#/.NET in production environments. Strong command of SQL and relational database design. Deep understanding of software engineering principles and architecture patterns. Excellent written and verbal communication skills. Experience mentoring or managing developers. Demonstrated ability to lead technical projects More ❯

analytics or engineering, within the financial services sector. Advanced proficiency in Power BI and Microsoft Dynamics 365 (including marketing and sales modules). Demonstrable full-stack development skills in SQL, Turbo C and Python, with proven experience in API development and data integration. Experience designing scalable data architectures and ETL pipelines. Proven ability to manage multiple priorities and deliver projects More ❯

Proficiency in cloud platforms (Azure, AWS, or GCP) and data processing services. Advanced skills in Power BI, including DAX, Power Query, and data modelling. Strong programming abilities in Python, SQL, and/or Scala. Expertise in ETL/ELT processes, data warehousing, and data mesh architectures. Familiarity with AI/ML concepts and their application in data analytics. Experience with More ❯

In conjunction with data colleagues, support the development of agency-wide data management processes to drive efficiency, quality and compliance Skills, experience, qualifications S kills Data manipulation and analysis SQL for querying and manipulation of structured customer and campaign data (mandatory) MS Excel including pivot tables, VLOOKUP, Power Query (mandatory) Python or R for advanced data manipulation, statistical analysis and More ❯

opportunities and solve data workflow challenges. Manage third-party vendors and consultants; oversee outsourced builds as needed. Core Skill Requirements Power BI : Strong experience building dashboards and data models. SQL : Comfortable writing and optimising queries for complex datasets. Python (or other scripting languages) : Exposure ideal; willingness to learn expected. Excel : Fluent, particularly for modelling and cross-functional reporting. Ability to More ❯