Data Engineer
- HashedIn
- 1 - 3 years
- Pune
- 27 days ago
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Job Description
POSITION
Senior Data Engineer / Data Engineer
Bangalore/Mumbai/Kolkata/Gurugra
m/Hyd/Pune/Chennai
LOCATION
EXPERIENCE
2+ Years
ABOUT HASHEDIN
We are software engineers who solve business problems with a Product Mindset for leading
global organizations.
By combining engineering talent with business insight, we build software and products that can
create new enterprise value.
The secret to our success is a fast-paced learning environment, an extreme ownership spirit,
and a fun culture.
WHY SHOULD YOU JOIN US?
With the agility of a start-up and the opportunities of an enterprise, every day at HashedIn,
your work will make an impact that matters.
So, if you are a problem solver looking to thrive in a dynamic fun culture of inclusion,
collaboration, and high performance HashedIn is the place to be!
From learning to leadership, this is your chance to take your software engineering career to the
next level.
So, what impact will you make?
Visit us @ https://hashedin.com
JOB TITLE: Senior Data Engineer / Data Engineer
OVERVIEW OF THE ROLE:
As a Data Engineer or Senior Data Engineer, you will be hands-on in architecting, building, and
optimizing robust, efficient, and secure data pipelines and platforms that power business-
critical analytics and applications. You will play a central role in the implementation and
automation of scalable batch and streaming data workflows using modern big data and cloud
technologies. Working within cross-functional teams, you will deliver well-engineered, high-
quality code and data models, and drive best practices for data reliability, lineage, quality, and
security.
HASHEDIN BY DELOITTE 2025
Mandatory Skills:
Hands-on software coding or scripting for minimum 3 years
Experience in product management for at-least 2 years
Stakeholder management experience for at-least 3 years
Experience in one amongst GCP, AWS or Azure cloud platform
Key Responsibilities:
Design, build, and optimize scalable data pipelines and ETL/ELT workflows using
Spark (Scala/Python), SQL, and orchestration tools (e.g., Apache Airflow, Prefect, Luigi).
Implement efficient solutions for high-volume, batch, real-time streaming, and event-
driven data processing, leveraging best-in-class patterns and frameworks.
Build and maintain data warehouse and lakehouse architectures (e.g., Snowflake,
Databricks, Delta Lake, BigQuery, Redshift) to support analytics, data science, and BI workloads.
Develop, automate, and monitor Airflow DAGs/jobs on cloud or Kubernetes, following
robust deployment and operational practices (CI/CD, containerization, infra-as-code).
Write performant, production-grade SQL for complex data aggregation,
transformation, and analytics tasks.
Ensure data quality, consistency, and governance across the stack, implementing
processes for validation, cleansing, anomaly detection, and reconciliation.
Collaborate with Data Scientists, Analysts, and DevOps engineers to ingest, structure,
and expose structured, semi-structured, and unstructured data for diverse use-cases.
Contribute to data modeling, schema design, data partitioning strategies, and
ensure adherence to best practices for performance and cost optimization.
Implement, document, and extend data lineage, cataloging, and
observability through tools such as AWS Glue, Azure Purview, Amundsen, or open-source
technologies.
Apply and enforce data security, privacy, and compliance requirements (e.g., access
control, data masking, retention policies, GDPR/CCPA).
Take ownership of end-to-end data pipeline lifecycle: design, development, code
reviews, testing, deployment, operational monitoring, and maintenance/troubleshooting.
Contribute to frameworks, reusable modules, and automation to improve
development efficiency and maintainability of the codebase.
Stay abreast of industry trends and emerging technologies, participating in code
reviews, technical discussions, and peer mentoring as needed.
Skills & Experience:
Proficiency with Spark (Python or Scala), SQL, and data pipeline
orchestration (Airflow, Prefect, Luigi, or similar).
Experience with cloud data ecosystems (AWS, GCP, Azure) and cloud-native services
for data processing (Glue, Dataflow, Dataproc, EMR, HDInsight, Synapse, etc.).
HASHEDIN BY DELOITTE 2025
Hands-on development skills in at least one programming language (Python, Scala, or
Java preferred); solid knowledge of software engineering best practices (version control, testing,
modularity).
Deep understanding of batch and streaming architectures (Kafka, Kinesis, Pub/Sub,
Flink, Structured Streaming, Spark Streaming).
Expertise in data warehouse/lakehouse solutions (Snowflake, Databricks, Delta Lake,
BigQuery, Redshift, Synapse) and storage formats (Parquet, ORC, Delta, Iceberg, Avro).
Strong SQL development skills for ETL, analytics, and performance optimization.
Familiarity with Kubernetes (K8s), containerization (Docker), and deploying data
pipelines in distributed/cloud-native environments.
Experience with data quality frameworks (Great Expectations, Deequ, or custom
validation), monitoring/observability tools, and automated testing.
Working knowledge of data modeling (star/snowflake, normalized,
denormalized) and metadata/catalog management.
Understanding of data security, privacy, and regulatory compliance (access
management, PII masking, auditing, GDPR/CCPA/HIPAA).
Familiarity with BI or visualization tools (PowerBI, Tableau, Looker, etc.) is an advantage
but not core.
Previous experience with data migrations, modernization, or refactoring legacy ETL
processes to modern cloud architectures is a strong plus.
Bonus: Exposure to open-source data tools (dbt, Delta Lake, Apache Iceberg, Amundsen,
Great Expectations, etc.) and knowledge of DevOps/MLOps processes.
Professional Attributes:
Strong analytical and problem-solving skills; attention to detail and commitment to code
quality and documentation.
Ability to communicate technical designs and issues effectively with team members and
stakeholders.
Proven self-starter, fast learner, and collaborative team player who thrives in dynamic,
fast-paced environments.
Passion for mentoring, sharing knowledge, and raising the technical bar for data
engineering practices.
Desirable Experience:
Contributions to open source data engineering/tools communities.
Implementing data cataloging, stewardship, and data democratization initiatives.
Hands-on work with DataOps/DevOps pipelines for code and data.
Knowledge of ML pipeline integration (feature stores, model serving, lineage/monitoring
integration) is beneficial.
HASHEDIN BY DELOITTE 2025
EDUCATIONAL QUALIFICATIONS:
Bachelors or Masters degree in Computer Science, Data Engineering, Information
Systems, or related field (or equivalent experience).
Certifications in cloud platforms (AWS, GCP, Azure) and/or data engineering (AWS Data
Analytics, GCP Data Engineer, Databricks).
Experience working in an Agile environment with exposure to CI/CD, Git, Jira,
Confluence, and code review processes.
Prior work in highly regulated or large-scale enterprise data environments (finance,
healthcare, or similar) is a plus.
HASHEDIN BY DELOITTE 2025
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data EngineerEmployement Type: Full timeContact Details:
Company: HashedInLocation(s): Pune
Keyskills: Pyspark Star Schema Spark Programming Hadoop Snow Flake Schema
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