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Senior Data Engineer
Sparibis Washington, DC
$124k-156k (estimate)
Full Time 1 Month Ago
Save

Sparibis is Hiring a Remote Senior Data Engineer

Location: 100% Remote

Years’ Experience: 10 years

Education: Bachelor’s in IT related field

Work Authorization: Must show that applicant is legally permitted to work in the United States.

Clearance: Applicants must be able to meet the requirements to obtain an Public Trust security clearance. NOTE: United States Citizenship is required to be eligible to obtain this security clearance.

Key Skills:

  • 10 years of IT experience focusing on enterprise data architecture and management
  • Experience with Databricks required
  • 8 years experience in Conceptual/Logical/Physical Data Modeling & expertise in Relational and Dimensional Data Modeling
  • Experience with Great Expectations or other data quality validation frameworks
  • Experience with ETL and ELT tools such as SSIS, Pentaho, and/or Data Migration Services
  • Advanced level SQL experience (Joins, Aggregation, Windowing functions, Common Table Expressions, RDBMS schema design, Postgres performance optimization)
  • Experience with AWS environment, CI/CD pipelines, and Python (Python 3) a bonus

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.

Qualifications

  • 10 years of IT experience focusing on enterprise data architecture and management
  • Experience in Conceptual/Logical/Physical Data Modeling & expertise in Relational and Dimensional Data Modeling
  • Experience with Databricks, Structured Streaming, Delta Lake concepts, and Delta Live Tables required
    • Additional experience with Spark, Spark SQL, Spark DataFrames and DataSets, and PySpark
    • Data Lake concepts such as time travel and schema evolution and optimization
    • Structured Streaming and Delta Live Tables with Databricks a bonus
  • Experience leading and architecting enterprise-wide initiatives specifically system integration, data migration, transformation, data warehouse build, data mart build, and data lakes implementation / support
    • Advanced level understanding of streaming data pipelines and how they differ from batch systems
    • Formalize concepts of how to handle late data, defining windows, and data freshness
    • 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.
    • Familiarity and/or expertise with Great Expectations or other data quality/data validation frameworks a bonus
    • Understanding of streaming data pipelines and batch systems
    • Familiarity with concepts such as late data, defining windows, and how window definitions impact data freshness
  • Advanced level SQL experience (Joins, Aggregation, Windowing functions, Common Table Expressions, RDBMS schema design, Postgres performance optimization)
    • Indexing and partitioning strategy experience
  • 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
  • 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
    • Ability to write and maintain Jenkinsfiles for supporting CI/CD pipelines
    • Experience working with AWS Lambdas for configuration and optimization
    • Experience working with DynamoDB to query and write data
    • Experience with S3
  • Knowledge of Python (Python 3 desired) for CI/CD pipelines a bonus
    • Familiarity with Pytest and Unittest a bonus
  • 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
  • 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

About Sparibis

Sparibis LLC is a professional solution firm that Clients rely on to access the best talent to drive their business success.

Sparibis is an equal opportunity employer that values diversity at all levels. All individuals, regardless of personal characteristics, are encouraged to apply.

Job Summary

JOB TYPE

Full Time

SALARY

$124k-156k (estimate)

POST DATE

03/16/2024

EXPIRATION DATE

05/15/2024

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The job skills required for Senior Data Engineer include Initiative, etc. Having related job skills and expertise will give you an advantage when applying to be a Senior Data Engineer. That makes you unique and can impact how much salary you can get paid. Below are job openings related to skills required by Senior Data Engineer. Select any job title you are interested in and start to search job requirements.

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The following is the career advancement route for Senior Data Engineer positions, which can be used as a reference in future career path planning. As a Senior Data Engineer, it can be promoted into senior positions as a CAE Designer IV that are expected to handle more key tasks, people in this role will get a higher salary paid than an ordinary Senior Data Engineer. You can explore the career advancement for a Senior Data Engineer below and select your interested title to get hiring information.

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If you are interested in becoming a Senior Data Engineer, you need to understand the job requirements and the detailed related responsibilities. Of course, a good educational background and an applicable major will also help in job hunting. Below are some tips on how to become a Senior Data Engineer for your reference.

Step 1: Understand the job description and responsibilities of an Accountant.

Quotes from people on Senior Data Engineer job description and responsibilities

The Senior Data Engineer builds data processing frameworks that handle the business’s growing database.

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The Senior Data Engineer owns and extends the business’s data pipeline through the collection, storage, processing, and transformation of large data-sets.

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Create architecture for real-time, big data applications with minimal maintenance effort.

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Provides successful deployment and provisioning of data solutions to production or other required environments.

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Step 2: Knowing the best tips for becoming an Accountant can help you explore the needs of the position and prepare for the job-related knowledge well ahead of time.

Career tips from people on Senior Data Engineer jobs

Apply for an entry-level data engineer role and gain experience.

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Earn a bachelor’s degree related to data engineering and begin working on projects.

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Consider pursuing additional professional engineering or big data certifications.

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Gain knowledge with new data architecture principles and concepts, thorough understanding of layered systems architectures.

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Senior data engineers should also have an understanding of other programming languages that help with statistical analysis and modeling, such as Python.

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Step 3: View the best colleges and universities for Senior Data Engineer.

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