Over 5 years of experience in SQL Server ETL development utilizing SSIS, Azure Data Factory, and Azure Databricks, with strong expertise in ETL, data warehousing, and T\-SQL.
Comprehensive understanding of data warehouse and data mart architectures, including the Kimball methodology.
More than 5 years of practical experience in building large\-scale databases.
Designing, developing, and deploying efficient and reliable data pipelines for data movement and transformation.
Wide\-ranging knowledge and hands\-on experience in data modeling, data management, ETL, and business intelligence (BI).
Expertise in building enterprise data warehouses incorporating table partitioning, encryption, and data compression techniques.
Experience with cloud migration initiatives.
Conduct ongoing monitoring, automation, and optimization of reports and BI solutions.
Collaborate with BI management to identify and resolve data\-related challenges.
Partner with business units to define and document requirements for new metrics and reports.
Participate in process evaluations and improvements.
*Other:**
Ensure adherence to established documentation standards and best practices.
Maintain strong business functional knowledge alongside up\-to\-date expertise in automated technologies and tools.
Comply with all policies and procedures related to confidential information, including internal and restricted data.
*Qualifications:**
*Required**
Minimum 7 years of experience as a Data Engineer on Enterprise Data Warehousing (DWH) and Business Intelligence (BI) projects, both on\-premises and cloud (Azure), with at least 3 years of hands\-on experience using Microsoft technologies such as SQL Server, Synapse, SSIS, Data Factory, and Databricks.
Proficiency in scripting languages such as Python, C\#, or their equivalents.
Advanced experience with MS SQL Server, MySQL, or Oracle databases.
Familiarity with Big Data technologies including NoSQL databases, Hive, HBase, Pig, or Spark.
Practical experience in ETL development using SSIS and Data Factory.
In\-depth knowledge of Master Data Management, ETL, data quality, metadata management, data profiling, micro\-batching, and streaming data ingestion.
Experience working with one or more scalable (MPP) relational databases such as Synapse or Snowflake for advanced analytics workloads.
Knowledge of application and system availability, scalability, and distributed data platforms.
Strong background in data warehousing technologies and ETL/ELT implementations.
Familiarity with the full Software Development Life Cycle (SDLC).
Experience working within Lean or Agile development methodologies.
*Desired**
Experience in defining new architectural frameworks and leading independent projects from an architectural perspective.
Familiarity with data modeling and ETL tools such as Erwin and Talend.
Ability to support users by troubleshooting and tuning queries, including partitioning and bucketing recommendations.
Experience designing and implementing ETL/ELT frameworks for complex warehouses and marts, with knowledge of large data sets, performance tuning, and troubleshooting.
A hands\-on development approach with a willingness to address and resolve complex technical issues.
Exposure to Continuous Integration / Continuous Deployment (CI/CD) processes.
Excellent verbal and written communication skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.