SSIS and Azure Data Engineer

Primary Duties and Responsibilities:

• 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.
• Provide analysis and resolve issues reported by business stakeholders.
• Engage in the design and delivery of cubes, dashboards, and a variety of self-service BI solutions.

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.
• Proven ability to provide technical leadership and mentor other engineers on best practices within data engineering.

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.