// TECHNICAL SKILL PROFILE
SQL

SQL & Database Engineering

25+ years architecting, tuning, and automating enterprise-grade relational databases at AT&T, Verizon, and TEOCO — from billing systems handling 24/7 cycles to multi-terabyte analytics pipelines.

Oracle DB SQL Server PL/SQL ETL Pipelines Performance Tuning SOX Compliance
25+ Years DB Experience
30% Operational Visibility ↑
1M+ Files Archived / Day
25% Query Latency Reduction
01

Core Competencies

💾

Relational Databases

  • Oracle Database (9i–19c)
  • Microsoft SQL Server
  • Schema design & normalization
  • Partitioning strategies
  • Index optimization

PL/SQL & T-SQL

  • Stored procedures & packages
  • Triggers & cursors
  • Bulk collect / FORALL
  • Dynamic SQL
  • Exception handling
🔄

ETL & Data Pipelines

  • Automated ETL scripting
  • 3GPP data processing (HSS/HLR)
  • Metadata archiving (1M+ files/day)
  • Shell + SQL integration
  • Incremental load patterns
📊

Performance & Tuning

  • EXPLAIN PLAN / AWR reports
  • Query rewrite & hints
  • Table stats & histograms
  • Parallel query execution
  • Connection pool management
🔒

Security & Compliance

  • SOX compliance enforcement
  • Role-based access control
  • Audit trail management
  • Data masking & encryption
  • GRC activities
🛠️

Tooling & Integration

  • SQL*Plus / SQL Developer
  • SSMS / Azure Data Studio
  • PowerShell + SQL Server
  • HDFS / Hadoop integration
  • Ansible DB automation
02

Proficiency Levels

Oracle DB / SQL*Plus95%
PL/SQL — Stored Procedures & Packages92%
Microsoft SQL Server / T-SQL88%
ETL Design & Automation90%
Performance Tuning & Query Optimization87%
PowerShell / Shell DB Scripting85%
03

Code Samples

-- ============================================================
--  Automated ETL Procedure: 3GPP CDR Staging to Core
--  Platform: Oracle 19c | Context: AT&T / Verizon BSS
-- ============================================================

CREATE OR REPLACE PROCEDURE etl_load_cdr_records (
    p_batch_date   IN  DATE     DEFAULT SYSDATE,
    p_rows_loaded  OUT NUMBER
)
AS
    v_batch_id     NUMBER;
    v_count        PLS_INTEGER := 0;
    ex_no_data     EXCEPTION;

BEGIN
    -- Generate batch identifier
    SELECT etl_batch_seq.NEXTVAL INTO v_batch_id FROM DUAL;

    -- Bulk insert from staging to core via MERGE
    MERGE INTO cdr_core tgt
    USING (
        SELECT record_id, msisdn, call_type, duration_sec,
               TRUNC(call_ts) call_date, node_id
        FROM   cdr_staging
        WHERE  load_date = TRUNC(p_batch_date)
        AND    status = 'PENDING'
    ) src
    ON (tgt.record_id = src.record_id)
    WHEN MATCHED THEN UPDATE SET
        tgt.status = 'RELOADED', tgt.batch_id = v_batch_id
    WHEN NOT MATCHED THEN INSERT
        (record_id, msisdn, call_type, duration_sec,
         call_date, node_id, batch_id, status)
    VALUES
        (src.record_id, src.msisdn, src.call_type, src.duration_sec,
         src.call_date, src.node_id, v_batch_id, 'LOADED');

    v_count := SQL%ROWCOUNT;
    IF v_count = 0 THEN RAISE ex_no_data; END IF;

    UPDATE cdr_staging
       SET status = 'PROCESSED', batch_id = v_batch_id
     WHERE load_date = TRUNC(p_batch_date)
       AND status = 'PENDING';

    p_rows_loaded := v_count;
    COMMIT;

EXCEPTION
    WHEN ex_no_data THEN
        DBMS_OUTPUT.PUT_LINE('No records for batch date: ' || p_batch_date);
    WHEN OTHERS THEN
        ROLLBACK;
        RAISE;
END etl_load_cdr_records;
/
-- ============================================================
--  Billing Audit Query: SOX-Compliant Revenue Reconciliation
--  Platform: Oracle | Context: AT&T Cingular Billing Cycles
-- ============================================================

WITH daily_revenue AS (
    SELECT
        TRUNC(txn_timestamp, 'DD')          AS txn_date,
        account_type,
        SUM(charge_amount)                  AS gross_revenue,
        SUM(discount_amount)                AS total_discounts,
        COUNT(DISTINCT subscriber_id)       AS active_subs,
        SUM(CASE WHEN status = 'FAILED'
                 THEN charge_amount ELSE 0 END) AS failed_revenue
    FROM   billing_transactions
    WHERE  txn_timestamp >= ADD_MONTHS(TRUNC(SYSDATE, 'MM'), -1)
    GROUP BY
        TRUNC(txn_timestamp, 'DD'), account_type
),
variance_check AS (
    SELECT
        d.*,
        LAG(gross_revenue, 1) OVER
            (PARTITION BY account_type ORDER BY txn_date) AS prev_day_rev,
        ROUND(
            (gross_revenue - LAG(gross_revenue,1)
                OVER(PARTITION BY account_type ORDER BY txn_date))
            / NULLIF(LAG(gross_revenue,1)
                OVER(PARTITION BY account_type ORDER BY txn_date), 0)
            * 100, 2
        ) AS day_over_day_pct
    FROM daily_revenue d
)
SELECT
    txn_date,
    account_type,
    TO_CHAR(gross_revenue, '$999,999,990.00')  AS gross_rev,
    TO_CHAR(total_discounts, '$999,999,990.00') AS discounts,
    active_subs,
    day_over_day_pct                              AS dod_variance_pct,
    CASE WHEN ABS(day_over_day_pct) > 15
         THEN '⚠ FLAG FOR REVIEW'
         ELSE 'OK'
    END AS audit_status
FROM  variance_check
WHERE failed_revenue / NULLIF(gross_revenue, 0) > 0.02
   OR  ABS(day_over_day_pct) > 15
ORDER BY txn_date DESC, account_type;
-- ============================================================
--  Performance Tuning: Index Strategy + Query Rewrite
--  Platform: SQL Server | Context: Verizon App Support
-- ============================================================

-- BEFORE: full table scan on 200M-row incident table (12.3s)
-- SELECT * FROM incidents WHERE app_id = 'VZ-CORE' AND sev = 1

-- STEP 1: Composite covering index
CREATE NONCLUSTERED INDEX IX_incidents_app_sev_ts
    ON dbo.incidents (app_id, severity_level, created_ts DESC)
    INCLUDE (incident_id, title, assigned_team, resolved_ts)
WITH (ONLINE = ON, FILLFACTOR = 85);

-- STEP 2: Rewritten query using CTE + filtered window
WITH recent_sev1 AS (
    SELECT
        incident_id,
        title,
        assigned_team,
        created_ts,
        resolved_ts,
        DATEDIFF(MINUTE, created_ts, ISNULL(resolved_ts, GETDATE())) AS mttr_min,
        ROW_NUMBER() OVER (
            PARTITION BY assigned_team
            ORDER BY     created_ts DESC
        ) AS rn
    FROM   dbo.incidents WITH (NOLOCK)
    WHERE  app_id         = N'VZ-CORE'
      AND  severity_level = 1
      AND  created_ts    >= DATEADD(DAY, -30, GETDATE())
)
SELECT
    assigned_team,
    COUNT(*)                                     AS incident_count,
    AVG(CAST(mttr_min AS DECIMAL(10,2)))         AS avg_mttr_min,
    MAX(mttr_min)                                AS worst_mttr_min,
    MIN(CASE WHEN resolved_ts IS NULL
             THEN 1 ELSE 0 END)               AS open_incidents
FROM  recent_sev1
GROUP BY assigned_team
HAVING   COUNT(*) > 2
ORDER BY avg_mttr_min ASC;
-- AFTER: 0.4s execution — 30x improvement using covering index
04

Database Experience Timeline

Verizon
2020 – 2025

Tier 2 Production / App Support Engineer

  • Developed automated ETL scripts and PL/SQL queries that increased operational visibility by 30% across 72+ enterprise applications
  • Maintained SQL-backed runbook automation tied to Ansible/Jenkins, reducing Sev-1 MTTR by 85%
  • Optimized Oracle and SQL Server queries for BSS/CRM platforms running on Apache WebLogic
TEOCO Corp
2013 – 2019

Senior Systems Integration Engineer

  • Led database migration for AT&T Linux platform transitions, cutting resolution times by 80%
  • Maintained 98% SLA adherence managing BSS billing and CRM systems with complex PL/SQL packages
  • Built ETL automation pipelines integrating Oracle schemas with HDFS for telecom analytics
AIRCOM / TEOCO
2009 – 2013

Database Architect

  • Implemented metadata archiving system processing 1M+ files daily — enhanced retrieval efficiency dramatically
  • Developed HDFS-backed storage solutions reducing query latency by 25%
  • Designed Oracle schemas for GSM/UMTS/LTE OSS solutions across multi-vendor VMware deployments
AT&T
1999 – 2009

Implementation Solutions Engineer

  • Designed custom billing tools for AT&T and Cingular Wireless using Oracle and Shell scripting, supporting 24/7 billing cycles
  • Performed complex ETL processing for 3GPP data (HSS/HLR/MME) repositories for strategic planning
  • Enforced strict SOX compliance and enterprise security protocols across all Oracle provisioning activities
05

Tools & Platforms

Oracle DB 9i–19c
SQL*Plus
SQL Developer
SQL Server 2012–2019
SSMS
Azure Data Studio
PL/SQL
T-SQL
PowerShell + SQLCMD
HDFS Integration
Kafka + Oracle CDC
Toad for Oracle
Kibana (ELK)
New Relic DB Monitoring
Ansible DB Modules
← Skills ⌂ Home