Sparibis is seeking a Data Engineer to join their team. The role involves planning, creating, and maintaining data architectures, ensuring alignment with business requirements while optimizing data processes and automating tasks where possible.

Responsibilities:

Plan, create, and maintain data architectures, ensuring alignment with business requirements
Obtain data, formulate dataset processes, and store optimized data
Identify problems and inefficiencies and apply solutions
Determine tasks where manual participation can be eliminated with automation
Identify and optimize data bottlenecks, leveraging automation where possible
Create and manage data lifecycle policies (retention, backups/restore, etc)
In-depth knowledge for creating, maintaining, and managing ETL/ELT pipelines
Create, maintain, and manage data transformations
Maintain/update documentation
Create, maintain, and manage data pipeline schedules
Monitor data pipelines
Create, maintain, and manage data quality gates (Great Expectations) to ensure high data quality
Support AI/ML teams with optimizing feature engineering code
Expertise in Spark/Python/Databricks, Data Lake and SQL
Create, maintain, and manage Spark Structured Steaming jobs, including using the newer Delta Live Tables and/or DBT
Research existing data in the data lake to determine best sources for data
Create, manage, and maintain ksqlDB and Kafka Streams queries/code
Data driven testing for data quality
Maintain and update Python-based data processing scripts executed on AWS Lambdas
Unit tests for all the Spark, Python data processing and Lambda codes
Maintain PCIS Reporting Database data lake with optimizations and maintenance (performance tuning, etc)
Streamlining data processing experience including formalizing concepts of how to handle lake data, defining windows, and how window definitions impact data freshness

Requirements:

5+ years Professional Experience
Bachelor's Degree in IT related field
Applicants must be able to obtain and maintain a secret security clearance. United States Citizenship is required as part of the eligibility criteria to be able to obtain this type of security clearance
CompTIA Security +
5+ years of IT experience focusing on enterprise data architecture and management to include data flow charts, diagrams, and other technical documentation
Experience with Databricks, Structured Streaming, Delta Lake concepts, and Delta Live Tables required
Python development experience required
Experience with ETL and ELT tools such as SSIS, Pentaho, and/or Data Migration Services, and the ability to incorporate Python as required
Advanced level SQL experience (Joins, Aggregation, Windowing functions, Common Table Expressions, RDBMS schema design, Postgres performance optimization)
Proficiency using Git for version control, including repository management, branching, merging, and pull requests
Must have an active Secret security clearance
Experience in Conceptual/Logical/Physical Data Modeling & expertise in Relational and Dimensional Data Modeling
Knowledge of Python (Python 3.X) for CI/CD pipelines required
Advanced level understanding of streaming data pipelines and how they differ from batch systems
Advanced understanding of ETL and ELT and ETL/ELT tools such as SSIS, Pentaho, Data Migration Service etc
Understanding of concepts and implementation strategies for different incremental data loads such as tumbling window, sliding window, high watermark, etc
Debug, troubleshoot, design and implement solutions to complex technical issues
Experience with large-scale, high-performance enterprise big data application deployment and solution
Understanding how to create DAGs to define workflows
Ability to thrive in a team-based environment
Experience briefing the benefits and constraints of technology solutions to technology partners, stakeholders, team members, and senior level of management
Repository setup and management
Branching strategies (feature, develop, main)
Merging and resolving conflicts
Creating and reviewing pull requests
Commit best practices (clear messages, atomic commits)
Tagging and release management
Active CompTIA Security+ certification preferred. If selected, must be able to obtain a CompTIA Security+ certification prior to beginning supporting the program
Additional experience with Spark, Spark SQL, Spark DataFrames and DataSets, and PySpark
Structured Streaming and Delta Live Tables with Databricks a bonus
Familiarity with Pytest and Unittest a bonus
Familiarity and/or expertise with Great Expectations or other data quality/data validation frameworks a bonus
Familiarity with concepts such as late data, defining windows, and how window definitions impact data freshness
Familiarity with CI/CD pipelines, containerization, and pipeline orchestration tools such as Airflow, Prefect, etc a bonus but not required
Architecture experience in AWS environment a bonus
Familiarity working with Kinesis and/or Lambda specifically with how to push and pull data, how to use AWS tools to view data in Kinesis streams, and for processing massive data at scale a bonus
Experience with Docker, Jenkins, and CloudWatch
Experience working with AWS Lambdas for configuration and optimization
Experience working with DynamoDB to query and write data
Experience with S3
Experience working with JSON and defining JSON Schemas a bonus
Experience setting up and management Confluent/Kafka topics and ensuring performance using Kafka a bonus
Familiarity with Schema Registry, message formats such as Avro, ORC, etc
Understanding how to manage ksqlDB SQL files and migrations and Kafka Streams

Sparibis

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Engineering

Data Engineer