Contributes to standards around which others will operate. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Integrates subject matter and industry expertise within Lending (Mortgage and Personal Loans). Contributes to data analytics standards around which others will operate. Articulate the basic differences between datatypes (e.g. JSON/NoSQL, Relational etc.,). Basic implications of different implementation decisions (e.g., distributed processing, parallel processing). Designing and implementing a data schema (e.g., normalization/de-normalization, relational model vs dimensional model, partitioning). Monitor and troubleshoot operational or data issues in the data pipelines. Experience with big data processing technology (e.g., Hadoop, Apache Spark, Pyspark, Python, Scala, HDFS, Hive, Impala etc.,), data warehouse technical architecture, infrastructure components, and reporting/analytic tools and environments. Big Data Platforms: Cloudera / Horton Works / Snowflake / AWS EMR / RedShift/ AWS Glue. Database, data warehouse or data lake solutions. Experience building data pipelines or automated ETL processes. One or more scripting language (e.g., Python, Scala, Shell Scripting). Experience with Build Tools, Version Control, Unit Test, Monitoring, Change Management to support DevOps. Scheduling tools like Autosys, Airflow etc., Knowledge of writing and optimizing SQL queries with large-scale, complex datasets. Data visualization tools like Tableau, Cognos, Qlickview, AWS QuickSight etc Familiarity with any NOSQL databases (HBase, MongoDB, Couchbase, Cassandra, and Neo4j) will be a plus. 6+ years' experience using tools for Data warehousing, Data Lake and cloud technologies Good team player by aiding the team with troubleshooting, researching the root cause, and thoroughly resolving issues in the event of a problem. Good Collaboration skills to work with Business Analysts, Data Engineers, Data Governance team, and other internal partners to identify opportunities/problems. Must be a self-starter with a positive attitude. Bachelor's/University degree, Master's degree preferred