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Data Engineer

Client Development / Client Delivery | Alpharetta, GA | Full Time

Job Description


We marry design and engineering language in ways that produce impactful and memorable experience journeys. We partner all the way to continuously improve our clients’ digital maturity. Our Studio network brings the optimal combination of skill, scale, and cost for each stage of the product development lifecycle. And to do this we need great transformational people that want to impact the projects and organizations that they work with. 

We are looking for an exceptional Data Engineer to work with our cross-functional team, and join our world-class community of talented experts. Core to this need are expertise in:

  • Batch Processing - capability to design an efficient way of processing high volumes of data where a group of transactions is collected over a period of time
  • Data Integration (Sourcing, Storage and Migration) - capability to design and implement models, capabilities and solutions to manage data within the enterprise (structured and unstructured, data archiving principles, data warehousing, data sourcing, etc.).  This includes the data models, storage requirements and migration of data from one system to another.
  • Data Quality, Profiling and Cleansing - capability to review (profile) a data set to establish its quality against a defined set of parameters and to highlight data where corrective action (cleansing) is required to remediate the data.
  • Stream Systems - capability to discover, integrate, and ingest all available data from the machines that produce it, as fast as it’s produced, in any format, and at any quality.


  • Lead the design, development and implementation of processes to extract, transform and load data from disparate sources into a form that is consumable by analytics processes within a given project, reviewing deliverables to ensure high quality
  • Evaluate and resolve issues regarding data quality reviews, cleansing, data integration and migration, leveraging advanced technical knowledge and showing technical leadership in aspects of data engineering while driving continuous improvement efforts
  • Ensure the appropriate expectations, principles, structures, tools and responsibilities are in place to deliver the project
  • Analyze the latest industry trends such as cloud computing and distributed processing and infer potential impact on the business (short and long-term)
  • Provide advanced technical expertise to maximize efficiency, reliability and value from current data engineering processes and research and monitor existing client base and industry developments to identify potential new product opportunities from emerging technologies
  • Develop strong working relationships with peers across engineering, collaborating to develop leading data engineering solutions
  • Drive adherence to the relevant data engineering and data modelling processes, procedures, standards, and provide input into the definition, maintenance and implementation of technology standards

Domain Knowledge

  • Business Information Glossaries: IBM Business Glossary, Azure data catalogue, SAP Information Steward
  • Cloud Computing: AWS, Azure, Google cloud, Oracle Cloud, Accenture cloud platform, Mulesoft CloudHub, Red Hat Cloud, IBM Infosphere Information Server, IBM Infosphere Warehouse Edition
  • Distributed Systems: Hadoop, HDFS, MapReduce/Hive, Storm, Spark, Cloudera, Hortonworks, MAPR, Hive, Hbase, Zookeeper, Elasticsearch
  • ETL Tools: SSIS, Informatica, SAP Data Services, IBM DataStage, Talend, Oracle Data Integrator, Alteryx
  • Graph Databases: Neo4j, Azure Cosmos, Titan, DataStax Enterprise Graph, Teradata, Aster, ArangoDB, InfiniteGraph, IBM Graph
  • In Memory Databases: SAP HANA
  • Monitoring: Splunk
  • NoSQL Columnar Stores: AWS RedShift, Accumulo, Cassandra, Druid, HBase, Vertica, SAP HANA
  • NoSQL Document Stores: Apache CouchDB, ArangoDB, Clusterpoint, Couchbase, DocumentDB, HyperDex, IBM Domino, MarkLogic, MongoDB, OrientDB, Qizx, RethinkDB
  • NoSQL Key Value Pair Data Store: DovetailDB, Oracle NoSQL Database, Dynamo, Riak, Dynomite, MotionDb, Voldemort, SubRecord, ArangoDB, Flare, Keyspace, RAMCloud, SchemaFree, Hyperdex, Aerospike, quasardb
  • Programming Languages: Java, Node.js, Powershell, Visual Studio, Shell Scripting, R, Scala, Pig, Hive, CSS, HTML5, XML, Sass, C++, C#, JavaScript, Python, Ruby, SQL
  • Relational MMP Databases: Teradata, Netezza
  • Relational SMP Databases: Oracle, IBM DB2, SQL Server, Azure SQL PaaS, MySQL

Ideally you will also have:

  • Undergraduate Degree in Computer Science, Physics or Mathematics (Graduate Degree always is a plus)
  • 7-10 years experience in Data Engineering
  • An Agile mindset with experience working in Agile environment
  • A spirit of collaboration and transparent communication
  • A natural curiosity for new scripting languages , frameworks and technologies 
  • High personal code/development standards (peer testing, unit testing, documentation, etc)

We are a thriving Community of top technology talent that is globally connected. We Engage, Make, Run and Evolve the technology that makes many brands that you know and love. So let’s take this journey together. No matter where you are on your digital career roadmap, we can help you grow and have fun doing it. 

Pack and move relocation available. Softvision LLC is an Equal Opportunity Employer. No 3rd Party Agency Candidates.