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·        Design, build and maintain ETL/ELT pipelines across multiple systems

·        Design and optimize data models in PostgreSQL, MongoDB, and Amazon Redshift

·        Develop and manage data workflows using AWS (S3, Glue, Lambda, Step Functions, Kinesis)

·        Administer and maintain database environments across development, staging, and production

·        Monitor data pipelines and databases, troubleshoot issues, and implement alerts

·        Optimize query performance, indexes, and configurations across relational and NoSQL systems

·        Manage database provisioning, upgrades, backups, and disaster recovery (RDS, MongoDB, Redshift)

·        Ensure database security, including access control, encryption, and role management

·        Plan capacity and scale systems to support growing data needs

·        Define and enforce data retention and archival policies

·        Collaborate with analytics and product teams to support reporting and data needs

·        Document data pipelines, database processes, and operational procedures

·        Participate in code reviews and follow engineering best practices

Required Education and Experience:

Bachelor’s degree in Computer Science, Engineering, or a related field — or equivalent experience.

3-5 years of Data Engineering Experience or equivalent experience

Qualifications:

·        3–5 years of experience in data engineering, database administration, or similar roles

·        Strong experience with PostgreSQL, MongoDB, and Amazon Redshift

·        Solid SQL skills for both transactional and analytical workloads

·        Experience with AWS data and database services (S3, Glue, Lambda, RDS, Redshift, etc.)

·        Proficiency in Python or another scripting language

·        Experience with workflow orchestration tools (Airflow, Step Functions, etc.)

·        Hands-on database administration experience, including:

·        MongoDB (replica sets, sharding, indexing, backups)

·        Redshift (cluster management, query tuning, WLM, snapshots)

·        PostgreSQL (replication, performance tuning, connection pooling)

·        Familiarity with monitoring tools (CloudWatch, pgBadger, MongoDB Atlas, etc.)

·        Understanding of database security (encryption, auditing, least-privilege access)

·        Strong problem-solving and analytical skills

·        Ability to translate business needs into data solutions

·        Comfortable working in a fast-paced, collaborative environment

·        Clear communicator with both technical and non-technical audiences

·        Self-motivated with a focus on clean, maintainable code

Nice to Have

·        Experience with Kafka or Kinesis (streaming data)

·        Familiarity with dbt for data transformation

·        Knowledge of data lake/lakehouse architectures (Delta Lake, AWS Lake Formation)

·        Experience with Terraform or CloudFormation

·        CI/CD experience for data pipelines

·        Basic DevOps skills