Senior DevOps Engineer

Role

• Design, store, process, and maintain large-scale data systems and related infrastructure.
• Drive multiple projects from both operational and technical standpoints.
• Ideate and build PoVs/PoCs for new products and solutions that help drive business growth.
• Define, design, and implement data engineering best practices, strategies, and solutions.
• Act as a data architect guiding customers, teams, and the organization on tools, technologies, and best practices.
• Lead architecture discussions and align solutions with business needs, security requirements, and engineering best practices.
• Execute multiple end-to-end data engineering projects as a data architect.
• Demonstrate strong conceptual understanding of data warehousing, ETL, data governance, security, cloud computing, and batch & real-time data processing.
• Apply strong execution knowledge of data modeling, SQL/NoSQL databases, SDLC practices, unit testing, and functional programming.
• Understand and work with Medallion architecture patterns.
• Manage conversations with client stakeholders, understand requirements, and translate them into technical outcomes.

Required Skills and Experience  

• 4-6 years of relevant work experience.
• Strong proficiency in SQL and experience with query and code optimization.
• Experience working with at least one major cloud platform (AWS, Azure, or GCP).
• Working knowledge of ETL and orchestration tools such as IICS, Talend, Matillion, Airflow, ADF, AWS Glue, or GCP Composer.
• Working knowledge of OLTP databases (Postgres, MySQL, SQL Server, etc.).
• Working knowledge of data warehouses such as Snowflake, Redshift, Azure Synapse, Hive, or BigQuery.
• Proficiency in at least one data engineering programming language such as Python (or Scala / Java / Rust).
• Strong execution knowledge of data modeling concepts including star schema, snowflake schema, and fact/dimension tables.
• Proficiency in Spark and distributed data platforms such as Databricks, EMR, AWS Glue, or GCP Dataproc.
• Experience working with Kafka and real-time streaming systems.
• Strong understanding of data architecture patterns such as Lambda, Kappa, data harmonization, and CDP patterns.
• Strong knowledge of Git and CI/CD pipeline design for continuous delivery.
  • Experience with data and networking security including RBAC, secret management, key vaults, certificates, and VNet/subnet configurations.