Database Engineer III

eSimplicity•Columbia, MD

12d•$102,600 - $125,000•Remote

About The Position

eSimplicity is a modern digital services company that works across government, partnering with our clients to improve the lives and ensure the security of all Americans—from soldiers and veterans to kids and the elderly, and defend national interests on the battlefield. Our engineers, designers and strategists cut through complexity to create intuitive products and services that equip Federal agencies with solutions to courageously transform today for a better tomorrow for all Americans. We are seeking a skilled and motivated Sr. SQL Developer to join our innovative IT team. In this role, you will build, tune, and operate the database processing behind a mission-critical, data-centric financial system supporting the Federal Government in the healthcare domain. The ideal candidate will have deep hands-on experience with Oracle SQL and PL/SQL at scale, large file-based data exchange, and AWS, and will deliver accurate, well-documented results on a recurring production schedule.

Requirements

All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation.
Education: Bachelor's degree in computer science, information systems, or related field (or equivalent experience).
Experience: 5+ years of hands-on experience developing and supporting production Oracle database applications, including at least 3 years in a data warehouse, financial transaction processing, or regulatory reporting context.
Expert Oracle SQL and PL/SQL: packages, procedures, cursors, collections, BULK COLLECT/FORALL, dynamic SQL, exception handling, and job/error instrumentation
Query performance tuning: reading execution plans, indexing strategy, partitioned large tables, and working with datasets in the hundreds of millions of rows
Parsing and loading structured files inside the database: XML (XMLTYPE/XMLTABLE), delimited and fixed-width formats, SQLLoader, and external tables
Working knowledge of healthcare or financial EDI interchange (X12 834, 810, 820, 835, 824, or comparable)
Enterprise batch scheduling (IBM Workload Scheduler/TWS, Control-M, Autosys, or similar) and Linux shell scripting
Python for data automation and report generation
Git-based version control and AWS familiarity, particularly Oracle RDS and S3
Experience with agile methodologies: SAFe, Scrum
Working knowledge of DevSecOps practices including CI/CD, formal release management, and change control with documented test evidence
Proven ability to handle sensitive healthcare and financial data under federal security controls, including least-privilege access and no unauthorized data movement or storage, and to tune processing for reliability within fixed, time-boxed production windows.
Strong written and verbal communication; able to explain data discrepancies to non-technical business leads and government stakeholders.

Nice To Haves

Experience working in regulated/Government environments is a plus, especially in the healthcare domain
Familiarity with healthcare enrollment, claims, or payer financial data is a plus
Experience with Databricks, PySpark, or migrating Oracle workloads to a cloud data platform is a plus
Experience with analytical and BI tools (e.g., Power BI, Tableau, or Amazon QuickSight) is a plus
Experience mentoring junior developers is desired

Responsibilities

Production data delivery: own and execute a portfolio of recurring data validation and reporting processes, delivering accurate results on schedule.
Hands-on SQL/PL/SQL engineering: design, write, and maintain Oracle PL/SQL packages and procedures that ingest and validate large XML and EDI files, load staging and fact tables, produce outbound data files, and reconcile results across interfacing systems.
Ad-hoc data analysis: turn ad-hoc client data requests into correct, well-documented query results and extracts under short turnaround, and explain the numbers behind them.
Performance and reliability: tune queries against very large partitioned tables, diagnose and recover failed batch jobs, and replace manual, spreadsheet-based steps with automated, repeatable processes.
Release discipline: take changes through a formal release process with documented testing, security review, and approval gates, and support them in production afterward.
Knowledge transfer: document what you build so others can run it, mentor junior developers, and contribute to the modernization of reporting workloads onto modern cloud data platforms.