... Working with relational and NoSQL databases Ensuring data quality, consistency, and reliability Building data processing and transformation workflows Monitoring data pipelines and troubleshooting failures Supporting data warehouse and data lake environments Documenting data pipelines, schemas, and processes Collaborating with ...
... collaborate with developers to drive them to resolution. - 4+ years in Technologies such as Core Java, SQL, Selenium and Cucumber to write test scripts. - 4+ years of Data/File/Database and ETL/Data warehouse testing and proficient in testing all conversions – File to file, file to Database, database to file etc. - Experience debugging ...
... cost management).- Strong architectural thinking and clear technical communication; experience with high-autonomy, end-to-end ownership.- Neo4j or other graph database experience.- Snowflake/data warehouse experience with dbt or Airflow.- Optimizely or similar experimentation/feature-management platforms.- Salesforce integration ...
... expertise in designing and managing Snowflake data warehouses, including performance tuning and resource monitoring.- Proficiency in building modular and scalable data transformations using Data Build Tool (dbt).- Advanced capability in writing complex SQL and Python scripts to manipulate large datasets and automate data processing ...
... and high-performing data https://jobeax.com/link/mQ5U4eML8IBoZ42E Responsibilities :Data Architecture & Platform Strategy :- Define and implement enterprise data architecture leveraging Microsoft Fabric (Lakehouse, Data Warehouse, Data Factory, Real-Time Analytics).- Design modern data platform strategies including Medallion ...
... Snowflake schema designs; Solid ETL development, reporting knowledge based off intricate understanding of business process and measures; Knowledge of Snowflake cloud data warehouse, Fivetran data integration and dbt transformations is preferred; Knowledge of Python is preferred; Basic knowledge of SQL Server databases is required; ...
... architecture.- Distributed Computing: 10+ years of experience working with distributed data processing or modern cloud data platforms, with strong hands-on exposure to Databricks, Spark, Snowflake, or equivalent technologies.- Data Architecture: Strong understanding of Lakehouse/Warehouse architecture, Medallion Architecture, scalability, ...
... contributions directly influence how millions of customers shop for groceries. Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources into Amazon's data warehouse and data lake environments. Build and optimize data models that support reporting, analytics, and machine learning ...
... — ensuring the org, not the model, controls where sensitive data flows. Key Responsibilities - Own end-to-end architecture for ACDP: data warehouses, tenant data stores, lakes, and feature stores supporting analytics, ML, and AI agent use cases. - Design and build the tenant registry and tenant data warehouse layer that ...
... English communication skills. - Comfortable in a fast-paced, agile consulting environment. Distributed transformation frameworks (e.g. dbt, Snowflake, or modern warehouse experience. Working with documents or other unstructured data. Monks is the global, digital-first, data-driven, unitary operating brand of S4 Capital plc. ...
... of software/tools that would be nice to have, but not required: Experience with cloud-based data warehouse: Snowflake Experience with relational SQL and NoSQL databases Experience with object-oriented/object function scripting languages: Golang, Python, Java, C++, Scala, etc. Experience with big data tools: Experience with ...
... metadata platforms - Experience supporting data lake, warehouse, or enterprise data platform initiatives Enterprise data modeling - Financial domain knowledge - Data quality and governance alignment - Business-to-data translation - Financial data structures - Fund / LP / GP data models - SQL / NoSQL schema design Bachelor’s ...
... and maintain scalable data pipelines and management systems. Develop and optimize data pipelines using modern orchestration tools (e.g., Develop and maintain data warehouse transformations using dbt and modern data warehousing techniques such as dimensional modeling, incremental processing. Collaborate with data architects ...
... parameters, and dashboard publishing. - Familiarity with columnar/lakehouse table formats such as Apache Iceberg, Delta Lake, or Apache Hudi. - Solid understanding of data warehouse concepts: dimensional modeling, slowly changing dimensions, incremental vs. full loads. - Comfortable working independently with minimal day-to-day ...
... micro-partitioning, caching, and warehouse sizing. Cloud Engineering (AWS | Azure | GCP) Build and maintain solutions using cloud-native compute/storage components: Data Warehousing & Modeling Design enterprise-grade Data Warehouses, Data Marts, and Semantic Layers. Implement Kimball, Data Vault, and modern ELT-first design patterns. ...
Data Engineer: PySpark+AWS Glue 4-8 years in Data Engineering with hands-on expertise in Snowflake, AWS Glue, AWS (S3/Lambda/CloudWatch), Python, PySpark, and SQL. Strong experience in ETL/ELT, Data Warehousing, Data Pipelines, Performance Tuning, and Cloud Data Platforms. Exposure to AI/ML or GenAI solutions is a plus ...
... interface performance during hypercare. Data From Process to Data Lake Data Validation & Process Improvement Support automation of CSV-Data upload by validation and data quality checks Perform data validation and cross-checks to ensure data quality and consistency Validate raw data and transform structured data to Data Model as ...
... contract and the Sponsor’s expectations. Core Responsibilities • Acts as Functional Lead for Data Management including primary contact for internal liaison between Data Management/Operations and Project Management, Clinical Monitoring, and other functional groups • Coordinate the work of the assigned Data Management/Data Operations ...
The Role You own the data substrate and the batch runtime of a product we are building from scratch. This is a data-specialist seat, not a general backend seat. Routine application development is guided in weekly reviews; what cannot be substituted is your depth in data modeling, set-based computation, and pipeline correctness. ...