251 to 275 of 8,354 SQL Jobs

willingness to help others • Experience scripting in the following preferred: o Python, Perl, and JavaScript in relation to Splunk Apps/Add-ons o SQL for querying structured data o Knowledge of XML and JSON for data handling o Splunk Search Processing Language (SPL) for data analysis in Splunk - What More ❯

willingness to help others • Experience scripting in the following preferred: o Python, Perl, and JavaScript in relation to Splunk Apps/Add-ons o SQL for querying structured data o Knowledge of XML and JSON for data handling o Splunk Search Processing Language (SPL) for data analysis in Splunk This More ❯

be able to perform statistical analysis. Requirements Python for DS (the usuals pandas plotting etc) Modelling skills for both ML applications and data reporting SQL at least basics but by year 3 should be quite proficient with at least pulling data Data Lake implementation and processing. Knowledge of Snowflake or More ❯

Able to design, build and deploy training approaches for the initiatives there are responsible for Technical Skills: Deep knowledge of PowerBI Deep knowledge of SQL Good knowledge of Power Automate Good knowledge of Paginated Reports Familiarity with Microsoft Fabric Familiarity with Insurance Industry Soft Skills: Proactive and focused on the More ❯

Able to design, build and deploy training approaches for the initiatives there are responsible for Technical Skills: Deep knowledge of PowerBI Deep knowledge of SQL Good knowledge of Power Automate Good knowledge of Paginated Reports Familiarity with Microsoft Fabric Familiarity with Insurance Industry Soft Skills: Proactive and focused on the More ❯

Inference Framework Experience (Ollama, LM Studio, etc.) Effective communication skills and the ability to work collaboratively in a team environment. Exposure to Database Technologies (SQL, Mongo, PostgreSQL, Redis, Etc.) Exposure to Natural Language Processing (NLP) techniques Exposure to Deep learning frameworks (e.g., TensorFlow, PyTorch) Experience with Docker containerization Experience with More ❯

on scalable architectures. Required Skills & Experience Experience: 3-5 years of hands-on experience with big data tools and frameworks. Technical Skills: Proficiency in SQL, Python, and data pipeline tools such as Apache Kafka, Apache Spark, or AWS Glue. Problem-Solving: Strong analytical skills with the ability to troubleshoot and More ❯

the boundaries of what’s possible with data analytics. What You Bring 5+ years in a Senior Data Analyst/Scientist role. Expertise in SQL and at least one analytical programming language (Python preferred, R or Julia acceptable). Strong background in data modelling (dimensional modelling), warehousing, and transformation techniques. More ❯

XHTML, Loopback Experience with Rest APIs,JSON, SOAP Experience with Docker and Kubernetes Experience with Code repositories, (i.e. GIT/SVN) Experience with Postgre SQL Experience with JIRA and Confluence Experience setting up and working with virtual environments, (VBOX, VM, Oracle) Experience with Windows, Solaris/Linux OS (scripting, command More ❯

to how your insights create business impact using platforms such as Tableau, Qlik, Power BI, RShiny, plotly, and d3.js. Working knowledge of databases and SQL is desired. Preferred qualifications include linking analytic and data visualization products to database connections. Preferred experience with data science methods related to data architecture, data More ❯

in data science Proficiency with data mining, mathematics, and statistical analysis Advanced experience in pattern recognition and predictive modeling Experience with Excel, PowerPoint, Tableau, SQL, and programming languages (ex: Java/Python, SAS) Ability to work effectively in a dynamic, research-oriented group that has several concurrent projects Proficiency in More ❯

data analysis, extraction, transformation, and loading, data intelligence, data security and proven experience in their technologies (e.g. Spark, cloud-based ETL services, Python, Kafka, SQL, Airflow) You have experience in assessing the relevant data quality issues based on data sources & uses cases, and can integrate the relevant data quality checks More ❯

vulnerability scanning tools (Nessus, Qualys) and security compliance frameworks (DISA STIGs, NIST, CIS benchmarks). Database & Log Analysis: Ability to query logs and databases (SQL, Splunk, ELK Stack) for troubleshooting patch failures. Required Qualifications: Bachelor's degree in computer science, Software Engineering, Information Technology, or a related field and More ❯

such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) - Experience in relational database technology (such as Redshift, Oracle, MySQL or MS SQL) - Experience in developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) - Experience in data engineering - Experience managing a More ❯

tools, including Power BI, Fabric, Azure Synapse, and DAX Strong understanding of cloud-based BI architectures and services (e.g., Azure, AWS, GCP) Experience with SQL, DAX, and Power Query Understanding of modern data warehouse concepts and ETL/ELT workflows Full driver's licence and access to a vehicle Curious More ❯

tools, including Power BI, Fabric, Azure Synapse and DAX Strong understanding of cloud-based BI architectures and services (e.g., Azure, AWS, GCP) Experience with SQL, DAX, and Power Query Understanding of modern data warehouse concepts and ETL/ELT workflows Full driver's licence and access to a vehicle Curious More ❯

tools, including Power BI, Fabric, Azure Synapse and DAX Strong understanding of cloud-based BI architectures and services (e.g., Azure, AWS, GCP) Experience with SQL, DAX, and Power Query Understanding of modern data warehouse concepts and ETL/ELT workflows Full driver's licence and access to a vehicle Curious More ❯

and Business Data Stewards to align data solutions with organizational objectives. Below are the key technical skills needed by a Senior Analytics Engineer: Advanced SQL expertise is essential for querying, transforming, and managing data within databases to support business insights. Proven experience in developing and optimising ETL/ELT pipelines More ❯

the digital advertising ecosystem. Expertise in data modeling, ETL pipelines, statistical analysis, and visualization tools (e.g., Tableau, Power BI). Hands-on experience with SQL, Python, R, or similar languages for data analysis. Familiarity with cloud platforms (e.g., AWS, Google Cloud) and big data tools (e.g., Spark, Snowflake). Exceptional More ❯

data modeling Hands-on experience with cloud-native data tech (preferably AWS: Redshift, Glue, S3, Lambda, IAM, Terraform, GitHub, CI/CD) Proficiency in SQL and Python for data processing and automation Experience working with data modeling tools and practices (e.g., dimensional, star/snowflake schema, dbt) Solid understanding of More ❯

Java, or C++. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with data processing tools and platforms (e.g., SQL, Apache Spark, Hadoop). Knowledge of cloud computing services (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes) is a plus. Hugging Face More ❯

Relevant experience in Data Platform Technologies, including Understanding of Databricks architecture, including basic data warehousing concepts and data sharing capabilities The ability to write SQL and/or Python queries for the purposes of transforming, joining and aggregating data Ability to analyse datasets and generate insights using Databricks analytical tools More ❯

mixture of utilizing the UI and writing M code. Developing calculations in DAX which are accurate and performant on large datasets. Proficient in writing SQL, MDX and M. Advanced tabular modelling and model administration via the XMLA endpoint, including knowledge of advanced tools, such as Tabular Editor and DAX Studio. More ❯

and compile architecture decision records (ADRs) Experience working in an agile team supporting and working with cross-functional teams Knowledge of relational (e.g., Postgres SQL) and non-relational databases (e.g., Graph database, Vector Database etc.) Familiarity in visualization technologies (e.g. Python DASH, Tableau, PowerBI) Proficiency in provisioning cloud infrastructure leveraging More ❯

/Experience (Essential): Prior experience in supporting Front Office trading booking and Risk systems. Working knowledge of Oracle SQL. (Able to build ad hoc SQL queries) Prior experience with UNIX plus an ability to navigate the system and core administration functions. (Able to navigate the system and write shell scripting More ❯