... https://jobeax.com/link/ylLUYLmAnFRP3UAj Qualifications : - 5+ years of experience in data engineering and building production-grade data pipelines.- Strong hands-on experience with data platforms such as Databricks.- Solid knowledge of data modeling, SQL, Spark, and Python.- Experience with orchestration frameworks, data quality tooling, and ...
... Purpose/ Summary We are looking for a skilled Data Engineer with 1-2 years of experience in designing, building, and maintaining scalable data pipelines and data platforms. The ideal candidate should have strong expertise in SQL, Databricks, and Azure Data Factory (ADF. and hands-on experience working with large datasets ...
... data problems and thrive in a fast-paced, collaborative environment, this one's for https://jobeax.com/link/F5wkEvjtX3G4ym8P You'll Do:- Build a self-service data platform for reporting & analytics.- Design robust data pipelines using Databricks, SQL, Python, Spark & Delta Lake on Azure (Blob Storage, Data Factory, Event ...
... Preparation Product Area, focused on building the next generation of finance data and processing services The team builds on a lakehouse architecture using Azure Databricks, Azure Data Factory and Azure Data Lake (Delta Lake) with Python being the main programming language and PySpark is used for large scale data engineering. ...
Responsible for conducting data analysis to extract actionable insights, exploring datasets to uncover patterns and anomalies, analyzing historical data for trend identification and forecasting, investigating data discrepancies, providing user training and support on data analysis tools, communicating findings through compelling ...
... observability for data systems. - Knowledge of data governance, metadata/catalogue tools, lineage and data quality frameworks (i.e. Strong grasp of security, data privacy and regulatory requirements (e.g., GDPR, data residency). - Professional certification such as Databricks or AWS (Solutions Architect / Specialty). Consulting ...
... - Solid understanding of data pipeline fundamentals, including ingestion, transformation, and loading (ETL/ELT) processes. - Must have experience with batch data processing (scheduling, dependencies, failure recovery, performance tuning). - Knowledge of data warehousing concepts and familiarity with relational databases. ...
Requirements Strong programming skills in Python and SQL. Experience with data processing leveraging programming skills in Python and Spark. In-depth understanding of the Kafka platform for (real-time) data ingestion and processing of high-volume data. Design and architect data flows and data management in a Cloud environment ...
... Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive ...
... governance principles, data quality checks on each data layer. - A successful history of manipulating, processing and extracting value from large disconnected datasets. - Working knowledge of message queuing, stream processing, and highly scalable big data data stores. - Strong project management and organizational skills. ...
... and mitigate data risks throughout the data lifecycle, including protection, retention, storage, use, and quality l Partner with technology teams to capture data sources, formats, and data flows so that data can be validated for downstream analytics and reporting l Investigate and document potential data quality issues, ...
... vector-based data pipelines for AI and GenAI use cases Develop scalable batch and streaming data pipelines using cloud-based data platforms (e.g., Snowflake or Databricks) Create and evolve semantic data models that transform raw data into analytics-ready, trustworthy datasets Build data preprocessing, validation, and quality-assurance ...
... teams to integrate predictive models into live production environments, ensuring low-latency performance and high reliability.- Conduct deep-dive exploratory data analysis on large-scale financial datasets to uncover hidden patterns that drive product strategy and business growth.- Partner with stakeholders to define key ...
... etc Design & develop data management and data persistence solutions for application use cases leveraging relational, non-relational databases and enhancing our data processing capabilities. Experience handling un-structured data, working in a data lake environment, leveraging data streaming and developing data pipelines driven ...
... support for personal https://jobeax.com/link/XUadz0hdkt5oLrCE :We are seeking a meticulous and proactive Security Analyst to join our security team. The Security Analyst will be responsible for monitoring, analyzing, and responding to security incidents to protect the organizations data and infrastructure. This role involves ...
Role Summary:Responsible for serving as the liaison between business and IT in translating complex business needs into application software. Analyzes complex end user needs to determine optimal means of meeting those needs and defines business application software requirements to address complex business needs.
... scalable products and automation solutions. The role serves as a bridge between clients, internal stakeholders, and technical teams to support solution delivery, data-driven decision-making, and continuous process improvement. It aligns with Business Analyst responsibilities and includes advanced exposure to analytical, reporting, ...
... pipelines, and developer tooling entirely on-premise. You'll build the core data infrastructure, tools, and internal products that enable hundreds of engineers, analysts, data scientists, and business teams to move faster. What You'll Do: Own product strategy, specs, and roadmaps for data platform components, APIs, and developer ...
... architectures like RNNs and LSTM , BERT Should have worked with cognitive services from major cloud platforms like AWS and have a working knowledge of SQL and no-SQL databases. Ability to create data and ML pipelines for more efficient and repeatable data science projects using MLOps principles Keep abreast with new tools, algorithms ...