Data Engineering Architect
About the Role
The Data Engineering Architect is responsible for providing the framework that appropriately replicates an organization’s big data needs utilizing data, hardware/software, cloud services, data engineers, and other IT infrastructure with the goal of aligning the IT assets of an organization with its business goals.
The Data Engineering Architect also provides support in identifying data gaps, building new data pipelines, and providing automated solutions to deliver advanced analytical capabilities and enriched data to applications that support the organization’s operations.
- Provide top-quality solution design and implementation for clients
- Provide support in defining the scope and the estimating of proposed solutions
- Engage with our clients to understand their strategic objectives
- Responsible for translating business requirements into technology solutions
- Work with the client and engagement leaders to define a project plan to meet delivery expectations
- Utilize Big Data technologies to architect and build a scalable data solution
- Identify any gaps and work with the client to resolve in a timely manner
- Stay current with technology trends in order to make useful recommendations to match the client requirements
- Responsible for the design and execution of abstractions and integration patterns (APIs) to solve complex distributed computing problem
- Participate in pre-sales activities, including proposal development, RFI/RFP response, shaping a solution from the client’s business problem.
- Act as a thought leader in the industry by creating written collateral (white papers or POVs), participate in speaking events, create/participate in internal and external events (lunch ‘n learns, online speaking events, etc.)
- 10+ years of hands-on professional development experience in architecting and implementing big data solutions is required
- 3+ years of strategic/management consulting is highly desired
- 3+ years of cloud experience (AWS, Azure or GCP) is required
- Strong hands-on experience using one or more ETL tools (Informatica, Talend, IBM DataStage, Azure Data Factory, AWS Glue, etc.) is required
- Experience with one or more on-prem or cloud databases (Snowflake, Redshift, Synapse, Teradata, Netezza, Oracle) is required
- Experience with Data Visualization tools (i.e. PowerBI, Tableau, Looker) is required
- Strong experience with big data tools and technologies and must be experienced in the following areas: Linux, Hadoop, Hive, Spark, HBase, Sqoop, Impala, Kafka, Flume, Oozie, MapReduce, etc.
- Ability to architect solutions using real-time/stream processing systems (i.e. Kafka, Kafka Connect, Spark, Flink, AWS Kinesis) is required
- Hands-on experience with scripting languages such as Java, Scala, Python, or Shell Scripting, etc. is required
- Expert level of expertise with SQL
- Hands-on Data Modeling skills using tools like ErWin, Visio or Enterprise
- Experience performing complex data migration to and from disparate data systems/platforms as well as to/from the cloud (AWS, Azure, GCP, etc.)
- Excellent knowledge of standard concepts, best practices, and procedures within a data warehousing and Business Intelligence (BI) environment
- Strong experience implementing Data Quality best practices and frameworks, including MDM and Data Governance)
- Excellent verbal and written communication skills
- Experience participating in pre-sales activities (i.e. proposal development, SOW creation, RFI/RFP responses, oral presentations, etc.)
- Bachelor or Master’s degree in Computer Science, Engineering or equivalent degree is required
- Must be open to 25% travel to the client location, as required by the client