V-Work Infotech Solutions INC

V-Work Infotech Solutions INC

Senior Data Engineer / Lead Data Engineer

Washington, District of Columbia, USA · Senior · Contract

Sponsorship not specifiedDetected 127 days ago
PythonGitSQLRedisElasticsearchBigQuerySnowflakeRedshiftDatabricksAWSGCPAzureCloud PlatformsDockerKubernetesTerraformCI/CDDevOpsKafkaMachine LearningSparkAirflowdbtData Engineering

Stay score

odds of building a lasting career here

40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

Lottery odds assume a STEM candidate.

Personalize to your clock →

Employer immigration record

from this employer's Department of Labor filings

Third-party placement is common here

59% of this employer's visa filings place the worker at a client company rather than at the employer itself, across 6 clients. Your visa, salary band and layoff exposure would follow the employer of record, not the client.Most common: CUMMINS TURBO TECHNOLOGIES · AT & T · Chevron Phillips Chemical Company LLC

Files H-1B transfers

6 transfer filings in the last year, covering 6 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

No reports yet — be the first to help the next applicant.

About the role

  • The ideal candidate should be comfortable working on a W2 basis and possess strong expertise in modern data engineering technologies and cloud platforms.
  • Ensure data quality, governance, security, and compliance standards.
  • Monitor, troubleshoot, and resolve production data issues.

Responsibilities

  • Design, develop, and maintain scalable ETL/ELT data pipelines.
  • Build and optimize enterprise data lakes, data warehouses, and data marts.
  • Develop batch and real-time data processing solutions.
  • Implement data integration solutions across multiple platforms and applications.
  • Collaborate with Data Scientists, Analysts, Product Owners, and Business Stakeholders.
  • Optimize database performance and large-scale data processing workflows.
  • Lead technical design discussions and mentor junior engineers.

Requirements

  • 12+ years of overall IT experience with strong Data Engineering expertise.
  • Advanced proficiency in Python, SQL, and/or Scala.
  • Extensive experience with Apache Spark, PySpark, Hadoop, Hive, and Kafka.
  • Strong expertise in ETL/ELT development and data pipeline architecture.
  • Hands-on experience with Databricks, Snowflake, Redshift, BigQuery, or Azure Synapse.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Strong understanding of Data Warehousing, Data Modeling, and Data Lake concepts.
  • Experience with Airflow, DBT, Azure Data Factory, Informatica, or Talend.
  • Experience with real-time streaming technologies such as Kafka, Spark Streaming, or Flink.
  • Knowledge of CI/CD, Docker, Kubernetes, Git, and DevOps practices.

Nice to have

  • Experience with Delta Lake and Lakehouse Architecture.
  • Experience with Terraform and Infrastructure as Code (IaC).
  • Cloud certifications (AWS, Azure, or Google Cloud Platform).
  • Nice-to-Have Skills Apache Flink Apache NiFi Elasticsearch Redis Data Mesh Architecture GenAI Data Pipelines Master Data Management (MDM) Employment Requirement Must be willing to work on a W2 basis.
  • No C2C or 1099 candidates.

Benefits

  • Knowledge of Machine Learning data pipelines and MLOps.
  • Experience working in Healthcare, Finance, Retail, or E-commerce domains.

This listing is sourced directly from V-Work Infotech Solutions INC's careers page and normalized into a canonical job model.