Database Engineer II- (Python,SQL,Automation)

As a

Database Engineer II

at

Tekion , you will design, automate, and optimize database operations across our cloud-native automotive retail platform connecting OEMs, dealerships, partners, and consumers.

This role requires strong expertise in

Python, SQL / PL-SQL, JavaScript (for MongoDB) , and

data structures & algorithms , with a deep focus on

problem-solving and automation .

Exposure to

AI / ML technologies

is a plus. Key Responsibilities

Python Automation (Primary Focus) :

Develop reliable and reusable Python scripts to automate key database operations such as schema migrations, health checks, data validation, and performance optimization.

SQL & PL / SQL Development :

Write and optimize

complex SQL queries ,

stored procedures ,

functions , and

triggers

for MySQL / PostgreSQL.

Develop and manage

PL / SQL logic

for data manipulation, validation, and reporting.

Perform schema design, indexing, and query plan optimization to enhance performance.

MongoDB Scripting : Use

JavaScript and Python

for MongoDB scripting, aggregation, data cleanup, and performance improvement tasks.

Algorithmic Problem Solving (Core Skill) :

Apply

data structures and algorithms

to solve real-world data and system challenges efficiently.

Design

Python-based programs

that automate or optimize database workflows using algorithmic thinking.

Example problem areas candidates should be comfortable with :

Finding duplicates or missing records in large datasets.

Comparing data consistency between source and target databases.

Implementing retry, queue, or scheduling logic using stacks / queues.

Detecting outliers or anomalies in performance metrics or logs.

Writing scripts to identify circular dependencies in database relationships.

Optimizing time complexity in Python scripts that process millions of records.

Designing scripts to summarize large log files or analyze trends.

Building mini utilities for automation — like config diff tools or schema comparison programs.

Monitoring & Troubleshooting :

Build monitoring automation to detect replication issues, latency spikes, or performance degradation and auto-trigger alerts or recovery actions.

DevOps & Cloud Integration :

Integrate with CI / CD pipelines and cloud services (AWS, Azure, GCP) to automate provisioning, deployment, and backups.

Performance Optimization :

Tune SQL queries, database configurations, and scripts for efficiency, scalability, and reliability.

Collaboration & Compliance :

Partner with DBAs, developers, and product teams to maintain operational standards, security, and compliance.

Qualifications & Skills

Must Have :

Strong proficiency in

Python

for automation, scripting, and algorithmic problem solving.

Hands-on expertise in

SQL and PL / SQL

for MySQL / PostgreSQL.

Proficiency in

JavaScript (for MongoDB)

scripting and operations.

Strong understanding of

Data Structures and Algorithms (DSA)

— arrays, linked lists, trees, graphs, hashing, recursion, etc.

Excellent analytical and debugging skills with a logical mindset.

Experience with

cloud platforms

(AWS, Azure, or GCP) and managed database services like RDS or DynamoDB.

Familiarity with

DevOps tools

(Git, Jenkins, Terraform, etc.).

Good communication skills and ability to collaborate across teams.

Nice to Have : Experience with

AI / ML integration , such as using models for anomaly detection or predictive performance insights.

Experience with database performance tuning, replication, or sharding.

Familiarity with monitoring and observability tools (Grafana, Prometheus, Datadog).

Knowledge of infrastructure automation (Ansible, Chef, Terraform).

Exposure to distributed database systems such as MongoDB Atlas or Aurora.

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.

What We’re Looking For

We’re seeking a

hands-on engineer

who : Codes efficiently in

Python, SQL, PL / SQL, and JavaScript .

Thinks algorithmically and solves complex problems creatively.

Automates repetitive database tasks with precision and scalability.

Understands both

SQL and NoSQL

performance tuning.

Brings curiosity, ownership, and innovation — including openness to

AI-driven solutions

for database management.