... 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 ...
... Java, JavaScript, or Python OR equivalent experience. Experience building scalable and highly available cloud services spanning multiple regions and/or clouds. Data modeling and big data processing experience Experience in work management and asset inventory systems #This position will be open for a minimum of 5 days, with ...
... 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. ...
... Bachelor's degree in Data Science, Computer Science, Statistics, Business Analytics, or related field. - Proven experience with SQL queries, database management, and data manipulation. - Hands-on experience with Power BI for creating dashboards, visualizations, and reports. - Basic understanding of data modeling and data warehousing ...
... 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 ...
... office environment. Duties may require extended periods of sitting and sustained visual concentration on a computer monitor or on numbers and other detailed data. Repetitive manual movements (e.g., data entry, using a computer mouse, using a calculator, etc.) are frequently required. Education & Experience - Bachelor's ...
... 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. ...
As an Associate in the Data Owner team, you will be expected to support processes and procedures that identify, monitor, and mitigate data risks throughout the data life cycle , in compliance with Firmwide policies and standards. Your role involves collaborating with technology and business teams to ensure that data is ...
... 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 ...
... 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 ...
... 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 ...
... candidate-screening and interviewing skills Ability to work independently from home Reliable internet connection and professional work-from-home setup Strong computer and data-entry skills Good knowledge of recruiting processes and candidate sourcing Strong work ethic and consistent attendance Ability to meet measurable productivity ...
... ownership, OR - 2-3 years as Data/Backend Engineer with PM work (PRDs, roadmaps, user research) Technical Stack Depth Deep understanding: ETL/ELT pipelines, data warehousing, data lakes/lakehouses Advanced SQL (query optimization, not just SELECT statements) Hands-on with ONE of: Hive/Spark/Hadoop/HDFS, Snowflake/Databricks/BigQuery, ...
... 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 ...