Database Engineer III

Primary Responsibilities

Utilize architectural and design skills for a variety of data-oriented tasks. 
Establish and maintain strong relationships with business stakeholders. 
Build highly reliable & scalable data systems with good data governance that provide complete, secure, accurate and timely data for analytics.
Expertise in data & dimensional modeling with good business acumen in supporting new product features and services - including financial reporting. 
Assist development and analytics organization to meet its delivery goals with regards to data design, flow and infrastructure. 
Perform Data Modeling, Big data architecture design, support and implementation of OLTP, real time OLAP/data warehouse systems and ETL pipelines. 
Track/Build & monitor data/system KPI’s like storage, performance & usage 
Hands on administration of big data databases/compute engines (Redshift, EMR, Spark or similar) and optimization/tuning techniques 
Prepare required documentation as outlined by departmental standards. 
Identify, analyze and back track data problems as needed. 
Provide recommendations for application and system improvements. 
Mentor other team members 
Work with business users to understand business requirements, issues and business and/or client processes. 
Develop, test, and maintain high-performance of our data systems to meet the requirements of the business and/clients while adhering to departmental standards. 
Perform quality assurance testing for all work performed. 
Meet with agile teams as required to define and document application requirements. 
Follow project development, deployment process & maintain industry standards and best coding practices. 
Maintain security and organization of the company’s data. 
Provide off-hour support as assigned. 
Gather business requirements/features, estimate the tasks, design & develop scalable solutions.
Work with manager to ascertain the company’s data requirements.
Plan work to meet project deadlines, accommodate demands by development teams, set priorities and escalate issues appropriately.
Provide recommendations to development teams for data restructuring and performing complex maintenance.
Deploy and manage changes in development, staging and production.
Assist development and dev ops teams on SQL queries and tuning.

Knowledge, Skills & Abilities

At least 7 years’ experience in data engineering, Data modeling, SQL, ETL, Big database, Data warehousing & basic-level administration of data infrastructure
At least 7 years coding experience in Java, Python, R or other equivalent programming language 
At least 4 years big data experience 
At least 2 years’ experience as technical lead architecting data lake/data warehouse/lake house systems & mentoring team of Data Engineers / DBAs 
Design, Development & implementation of OLTP & OLAP databases with efficient design, optimization techniques & data ingestion mechanisms.
Proficient in Python, SQL and PL-SQL, query tuning, optimization, ETL, ELT, Data Modeling and Data Warehouse systems.
Proficient in a variety of big-data tools and technologies, including Hadoop, Spark, etc., handling different storage formats like Parquet, Delta/Apache Hudi/Apache Iceberg
Experience building data lakes & warehouse systems leveraging cloud environments including AWS technologies –S3, Redshift, Aurora/RDS, DMS, EC2, Glue spark, Cloud watch, & EMR
Experience with data orchestration tools like Airflow 
Experience in building pipelines, ingesting data from heterogeneous systems onto data lake environments in real time
Proficient in Business Intelligence (BI), analytic database and products, able to take business requirements and translate into database tables, pipeline design and tasks.
General data-specific concepts, frameworks and processes 
Agile development practices 
Working within an SDLC 
Designing data warehouses including definition, structure, documentation, maintenance, long-range requirements, operational guidelines, and protection 
Data governance, meta data management, data security measures, retention & archival across data lake layers

Other Skills And Experience

Cloud experience, such as AWS, GCP or Azure 
Building/Managing data lake & lake house architectures.
Experience working on different data lake storage formats.
Excellent oral and written communication 
Multi-tasking and managing multiple priorities.
Working well in a team-oriented, collaborative environment with people from different disciplines and varying degrees of technical experience 
Working in an Agile team environment.